Target detection method and apparatus for lawn mower, electronic device and storage medium

Abstract

Embodiments of the present application provide a target detection method and apparatus for a lawn mower, an electronic device and a storage medium. The method comprises: acquiring a target frame set obtained by a target sensor detecting a sensor shell surface of the target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by the target sensor performing each detection, and the target sensor is a sensor configured on a lawn mower and used for generating a point cloud; performing a projection operation on the target frame set to obtain a target projection image, wherein the projection operation is an operation of performing projection on a specified plane; and inputting the target projection image into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model used for distinguishing a plurality of preset categories, and the target classification result is used for indicating a preset category among the plurality of preset categories matching the target frame set.

Description

Target detection method and device for lawn mower, electronic device and storage medium

[0001] This application claims priority to the Chinese patent application filed with the Patent Office of China on October 31, 2023, with application number 202311434816.0 and invention name “Target detection method and device, electronic device and storage medium for lawn mower” and the Chinese patent application filed with the Patent Office of China on August 13, 2024, with application number 202411110647.X and invention name “Target detection method and device, electronic device and storage medium for lawn mower”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to the field of computers, and more specifically, to a target detection method and device, an electronic device, and a storage medium for a lawn mower. Background Art

[0003] Currently, for some devices that need to be used outdoors or in other unobstructed scenarios, in order to avoid adverse effects of environmental factors on device operation, additional sensors can be added to detect these environmental targets. For example, a rain sensor can be used to detect rain, or a visible light sensor can be added to train a model for discrimination.

[0004] However, the above-mentioned method of performing target detection by adding redundant sensors requires setting the added sensors in specific locations based on the characteristics of the environmental targets to be detected, which not only increases the design difficulty and engineering costs, but also causes the equipment to be too large, affecting the user experience of the equipment.

[0005] It can be seen that the target detection method in the related art has the problems of high difficulty in equipment design and excessively large equipment size.

[0006] Summary of the Invention

[0007] The embodiments of the present application provide a target detection method and device, an electronic device, and a storage medium for a lawn mower, so as to at least solve the problems of high equipment design difficulty and excessive equipment size in target detection methods in related technologies.

[0008] According to one aspect of an embodiment of the present application, a target detection method for a lawn mower is provided, comprising: obtaining a target frame set obtained by detecting a sensor shell surface of the target sensor through a target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by a single detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; performing a projection operation on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; inputting the target projection image into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model for distinguishing multiple preset categories, and the target classification result is used to indicate a preset category among the multiple preset categories that matches the target frame set.

[0009] According to another aspect of an embodiment of the present application, a target detection device for a lawn mower is also provided, including: an acquisition unit, configured to acquire a target frame set obtained by detecting a sensor shell surface of the target sensor through a target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by a detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; a first execution unit, configured to perform a projection operation on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; an input unit, configured to input the target projection image into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model for distinguishing multiple preset categories, and the target classification result is used to indicate a preset category among the multiple preset categories that matches the target frame set.

[0010] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided. The lawn mower includes a laser radar. The method includes: after detecting bad weather through the laser radar, the lawn mower returns to a base station or continues to work.

[0011] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, wherein the lawn mower includes a laser radar, and the method includes: generating and sending weather information after detecting bad weather through the laser radar; and the lawn mower returns to the base station or continues to work after receiving the control signal.

[0012] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, which is applied to a base station. The method includes: after the base station receives weather information, sending a control signal to control the lawn mower to return to the base station or continue working.

[0013] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, which is applied to a user terminal. The method includes: after the user terminal receives weather information, sending a control signal to control the lawn mower to return to the base station or continue working.

[0014] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, wherein the lawn mower includes a laser radar, and the method includes: when there are water stains on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once, and judging the current weather based on the obtained water signal; controlling the lawn mower to perform corresponding actions according to the current weather; the controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is judged that the current weather is bad weather, performing a shielding action on at least part of the lawn mower.

[0015] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, wherein the lawn mower includes a laser radar, and the method includes: when there are water stains on the shell surface of the laser radar, obtaining water signals obtained by the laser radar detecting the shell surface at least twice within a set total time period, and determining the current weather based on the obtained water signals; controlling the lawn mower to perform corresponding actions according to the current weather; the controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is determined that the current weather is bad weather, performing a shielding action on at least part of the lawn mower.

[0016] According to another aspect of an embodiment of the present application, a lawn mower control method is also provided, wherein the lawn mower includes a laser radar, and the method includes: when there are water stains on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once; when the coverage value of a single water signal increased on the shell surface per unit time is greater than a preset value, controlling the lawn mower to continue mowing according to a preset cutting path and cutting mode.

[0017] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned target detection method for a lawn mower or the above-mentioned lawn mower control method when running.

[0018] According to another aspect of an embodiment of the present application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-mentioned target detection method for a lawn mower or the above-mentioned lawn mower control method through the computer program.

[0019] Through the embodiment of the present application, a target frame set is obtained by detecting the surface of a sensor shell of a target sensor through a configured sensor through the target sensor, wherein each target frame in the target frame set is a single frame point cloud obtained by a detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; a projection operation is performed on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; the target projection image is input into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model for distinguishing multiple preset categories, and the target classification result is used to indicate multiple preset categories. The preset category that matches the target frame set is based on the projection processing of the point cloud set (for example, the target frame set) obtained by detecting the surface of the sensor shell by the sensor, and the target recognition is performed on the projection image obtained by the projection using a classification model. It can adapt to the detection of one or more environmental targets, improve the universality of target detection, and have low requirements for the setting position of the sensor, which can reduce the difficulty of equipment design. At the same time, the sensor used can be a configured sensor for obstacle detection, and there is no need to add additional sensors. The technical effect of reducing the difficulty of equipment design and reducing the size of the equipment can be achieved, thereby solving the problems of high equipment design difficulty and excessive equipment size in the target detection method in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] FIG1 is a hardware structure block diagram of an optional lawn mower according to an embodiment of the present application;

[0021] FIG2 is a flow chart of an optional target detection method for a lawn mower according to an embodiment of the present application;

[0022] FIG3 is a schematic diagram of an optional target detection method for a lawn mower according to an embodiment of the present application;

[0023] FIG4 is a schematic diagram of another optional target detection method for a lawn mower according to an embodiment of the present application;

[0024] FIG5 is a flow chart of another optional target detection method for a lawn mower according to an embodiment of the present application;

[0025] FIG6 is a flow chart of another optional target detection method for a lawn mower according to an embodiment of the present application;

[0026] FIG7 is a structural block diagram of a target detection device for a lawn mower according to an embodiment of the present application;

[0027] FIG8 is a structural block diagram of a computer system of an optional electronic device according to an embodiment of the present application;

[0028] FIG9 is a flow chart of an optional lawn mower control method according to an embodiment of the present application;

[0029] FIG10 is a flow chart of another optional lawn mower control method according to an embodiment of the present application;

[0030] FIG11 is a flow chart of another optional lawn mower control method according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The embodiments of the present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0032] It should be noted that the terms "first", "second", etc. in the description and claims of the embodiments of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0033] The method embodiments provided in the embodiments of the present application can be executed in a lawn mower or a similar processing device. Taking operation on a lawn mower as an example, Figure 1 is a hardware structure block diagram of an optional lawn mower in an embodiment of the present application. As shown in Figure 1, the lawn mower may include one or more (only one is shown in Figure 1) engines 102, transmission components 104 and mowing parts 106 (for example, blades). In addition, for some intelligent lawn mowers, it may also include: a sensor 108, a processor 110 (the processor 110 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 112 for storing data, wherein the above-mentioned lawn mower may also include a transmission device and input and output devices for communication functions. It can be understood by those skilled in the art that the structure shown in Figure 1 is only for illustration and does not limit the structure of the above-mentioned lawn mower. For example, the lawn mower may also include more or fewer components than those shown in Figure 1, or have a configuration different from that shown in Figure 1.

[0034] The memory 112 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the target detection method for a lawn mower in the embodiment of the present application. The processor 110 executes various functional applications and data processing by running the computer program stored in the memory 112, that is, implementing the target detection method for a lawn mower described above. The memory 112 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 112 may further include a memory remotely located relative to the processor 110, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0035] The transmission device is used to receive or send data via a network. A specific example of the aforementioned network may include a wireless network provided by the lawn mower's communications provider. In one embodiment, the transmission device includes a NIC (Network Interface Controller), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device may be an RF (Radio Frequency) module, which is used to communicate with the Internet wirelessly.

[0036] According to one aspect of an embodiment of the present application, a target detection method for a lawn mower is provided. This method can be executed by a server or a lawn mower alone, by both the server and the lawn mower, or by a terminal device that has a direct or indirect communication connection with the lawn mower. Taking the lawn mower as an example of executing the target detection method for a lawn mower in this embodiment, FIG2 is a flow diagram of an optional target detection method for a lawn mower according to an embodiment of the present application. As shown in FIG2 , the flow includes the following steps:

[0037] Step S202 : acquiring a target frame set obtained by detecting the sensor housing surface of the target sensor through the target sensor.

[0038] The target detection method for a lawn mower in this embodiment can be applied to scenarios where target detection is performed on a lawn mower or similar equipment. The detected target can be an environmental target, and the environmental target can be a target in an outdoor environment that has an impact on the operation of the equipment, such as rain, dust, grass clippings or other targets, or a target that has an impact on the operation of the equipment in some special environments (inside a production workshop). Although the lawn mower is used as an example for illustration in this embodiment, the target detection method in this embodiment is also used for other similar equipment (represented by target equipment). In some examples of this embodiment, rain detection of a lawn mower (rain detection, for scenes with rain, the equipment will be exposed to rain) is used as an example for illustration.

[0039] Here, a lawn mower is also called a weeder, lawnmower, or lawn trimmer. A lawn mower is a mechanical tool used to trim grass and vegetation. It may include a cutterhead, an engine, running wheels, a running mechanism, blades, armrests, and controls. It can be an intelligent lawn mower, meaning it requires no manual control, or it can be an intelligently assisted manual control system. In this embodiment, the components of the lawn mower are not limited; they can be used as long as they can perform mowing and object detection functions.

[0040] In order to avoid the impact of adding redundant rain sensors on the difficulty of equipment design, equipment volume, etc., in this embodiment, the point cloud set obtained by detecting the surface of the sensor shell based on the sensor installed on the lawn mower can be projected, and the projection image obtained by the projection can be used for target recognition using a classification model. It can adapt to the detection of one or more environmental targets, improve the universality of target detection, and has low requirements for the setting location of the sensor, which can reduce the difficulty of equipment design. At the same time, the sensor used can be a configured sensor for obstacle detection, without the need to add additional sensors, which can reduce the difficulty of equipment design and reduce the size of the equipment.

[0041] A lawn mower may be equipped with a target sensor. This target sensor may be a sensor already installed on the mower (or a sensor configured to generate a point cloud), such as a sensor for obstacle detection. This sensor may be a laser radar sensor (referred to as a laser radar) or another type of sensor. The mower (or a processor thereon) may obtain a target frame set obtained by detecting the surface of the sensor housing via the target sensor. Each target frame in the target frame set is a single frame of a point cloud obtained by a single detection performed by the target sensor.

[0042] LiDAR is a device that measures distance and creates a three-dimensional point cloud map by transmitting laser beams and receiving reflected light. In this device, a laser scanner transmits a laser beam and records the time and location of reflected light, generating point cloud data. After the laser beam is reflected back to the device, it measures the time and location of the laser beam's transmission, thereby calculating the distance traveled by the reflected beam. By scanning the laser beam to capture reflected light in all directions in space, the device creates a point cloud in three-dimensional space.

[0043] For example, as shown in Figure 3, a LiDAR can include three major systems: laser emission, laser reception, and information processing. These three systems complement each other to form a closed sensing loop. Taking the use of lasers to model objects as an example, first, the excitation source in the laser emission system periodically drives the laser to emit laser pulses. The laser modulator controls the direction and number of laser lines emitted through the beam controller. Finally, the laser is emitted to the target object through the transmitting optical system. The scanning system is responsible for rotating at a stable speed to scan the plane and generate real-time plane map information. The photodetector in the laser receiving system receives the laser reflected back from the target object and generates a received signal. The received signal in the information processing system is amplified and converted from digital to analog. The information processing module calculates and obtains the surface morphology, physical properties, and other characteristics of the target, ultimately establishing an object model.

[0044] In this embodiment, the target frame set may include a point cloud set obtained by the target sensor performing multiple detections on the surface of the sensor shell within a certain period of time. The detection cycle of the target sensor on the surface of the sensor shell may be pre-configured, and the multiple detections may be continuous or non-continuous. The target frame set is not limited in this embodiment.

[0045] Optionally, the target sensor can be an integrated sensing device. In addition to performing point cloud detection, the target sensor can also be used for at least one of the following: navigation, positioning, obstacle avoidance, and the operations applied to navigation, positioning, obstacle avoidance, etc. can be performed based on the detected point cloud, but the processing logic and judgment method are different. In addition, the target sensor is also applicable to other operations that can be performed based on the detected point cloud.

[0046] Optionally, in order to facilitate target detection, the surface of the sensor shell can be a plane and / or a curved surface. The type of sensor shell surface can be flexibly selected for different detection targets to ensure the accuracy of target detection while avoiding the impact of target accumulation on the performance or service life of the equipment. The target sensor can be set at an angle to the horizontal plane at the front end area of ​​the top of the lawn mower. Here, the target sensor is set at an angle to the horizontal plane means that the detection center line of the target sensor is at a certain angle to the horizontal plane (that is, the target sensor has a certain inclination angle, for example, the inclination angle is 30 degrees), for example, 30 degrees, 45 degrees or other angles. The target sensor is set at an angle to the horizontal plane at the front end area of ​​the top of the lawn mower, and the detected area is in an upper position to avoid inaccurate detection results due to occlusion and other reasons (for example, curved surfaces).

[0047] For example, a lawn mower may be equipped with a laser radar with a protective shell, and the shell surface of the protective shell is flat or spherical, and the laser radar is installed at a certain tilt angle. Accumulate the laser radar point cloud for a total of n frames (n is a positive integer greater than or equal to 2): PointCloud sum ={frame1,frame2,...,frame i} frame i ={point1,point2,...,point j}

[0048] Among them, PointCloud sum It can be represented as a LiDAR cumulative point cloud (i.e., target frame set); frame i It can be expressed as a single-frame point cloud of the laser radar, 0≤i≤n; point j It can be represented as a lidar point, 0≤j≤m.

[0049] Step S204: performing a projection operation on the target frame set to obtain a target projection image.

[0050] In order to improve the convenience of target detection based on the target frame set, a projection operation can be first performed on the target frame set, that is, each position point in the target frame set is projected onto a specified plane, and the target frame set is converted into a two-dimensional image, so that target detection can be performed using an image detection method. The specified plane can be a horizontal plane or other planes. Here, for the projection method of the target frame set, the position point information of each position point in the target frame set can be used as the pixel value of the corresponding projection position (pixel position). If the projection positions of multiple position points are the same, the position point information of multiple position points with the same projection position can be fused. In this embodiment, there is no limitation on the projection method of the target frame set.

[0051] Optionally, performing the projection operation on the target frame set may involve directly converting the captured point cloud data into a projection image within a specified plane using the target sensor's built-in functionality, and then fusing the multiple converted projection images to obtain the target projection image. Alternatively, multiple single-frame point clouds captured may be accumulated to obtain the target frame set, and then the projection operation may be performed on the target frame set as a whole. Other projection operation methods are also possible and are not limited in this embodiment.

[0052] Step S206: input the target projection image into the trained target classification model to obtain a target classification result.

[0053] After obtaining the target projection image, the target projection image can be input into a trained target classification model to obtain a target classification result. The target classification model can be a classification model for distinguishing multiple preset categories, and the target classification result can be used to indicate the preset category among the multiple preset categories that matches the target frame set, that is, the preset category that matches the target projection image.

[0054] The target classification model can be a Convolutional Neural Network (CNN) or another type of classification model. Convolutional neural networks are a type of feedforward neural network with a deep structure that incorporates convolutional computations. They are a representative algorithm for deep learning. This type of method effectively leverages the mature network structure of two-dimensional images and utilizes massive amounts of annotated two-dimensional image data for pre-training, thereby achieving excellent classification results.

[0055] Optionally, multiple preset categories can be set based on the environmental targets to be detected. For example, for a scenario where only rain detection is performed, the multiple preset categories can include two types: rain and non-rain. Rain can be divided into multiple levels, for example, the first level (corresponding to light rain), the second level (corresponding to moderate rain), and the third level (corresponding to heavy rain). Other division methods are also possible, and each level can correspond to a preset category. In addition to rain, the detected environmental targets may also include dust, grass clippings, mud, etc. The preset categories may include the types, levels, etc. corresponding to these environmental targets, as long as the environmental targets to be detected and the levels of the environmental targets, etc. can be distinguished by the image features of the projected image.

[0056] Optionally, in order to improve the diversity of target detection, preset types can be configured for a variety of different environmental targets, and multiple preset categories are used to represent at least one of the following targets: rain, hail, snow, sandstorm, fog, etc. In addition, one or more levels can be set for each environmental target to indicate the intensity of the corresponding environmental target.

[0057] Through the above steps, a target frame set is obtained by detecting the sensor shell surface of the target sensor through the target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by a detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; a projection operation is performed on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; the target projection image is input into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model for distinguishing multiple preset categories, and the target classification result is used to indicate a preset category among multiple preset categories that matches the target frame set, thereby solving the problems of large equipment volume and high equipment design difficulty in the target detection method in the related art, reducing the difficulty of equipment design, and reducing the equipment volume.

[0058] In an exemplary embodiment, acquiring a target frame set obtained by detecting a sensor housing surface of a target sensor through a target sensor includes:

[0059] S11, acquiring multiple groups of echo signals obtained by transmitting a detection signal multiple times by the target sensor to the surface of the sensor housing, wherein each group of echo signals in the multiple groups of echo signals includes two echo signals corresponding to a single detection signal transmitted;

[0060] S12: Fusing the two echo signals in each group of echo signals into a corresponding single-frame point cloud to obtain a target frame set.

[0061] In this embodiment, when the target sensor detects the surface of the sensor housing, multiple sets of echo signals can be generated by the target sensor transmitting multiple detection signals to the sensor housing surface. The time interval between the detection signal transmissions can be fixed or variable. For each detection signal transmission, a set of echo signals can be obtained, with each set of echo signals containing two echo signals corresponding to the single detection signal transmission. In this embodiment, to ensure the rationality of target detection, one echo signal in each set of echo signals is an echo signal reflected from the sensor housing surface, and the other echo signal is an echo signal reflected from the detected target.

[0062] For example, according to the model of the laser radar, the original two echo data of the laser radar are used for processing, the first echo is the echo of the protective shell, and the second echo is the echo of the environmental target on the protective shell.

[0063] For each group of echo signals obtained, two of the echo signals can be fused into a corresponding single-frame point cloud to obtain a target frame set. The fusion method can be to calculate the difference between the two, or to fuse the two in combination with other information. In this embodiment, there is no limitation on the fusion method of the echo signals.

[0064] Through this embodiment, two echo signals obtained by transmitting a detection signal once are fused to obtain a single-frame point cloud in the target frame set, which can improve the convenience and accuracy of point cloud data acquisition.

[0065] In an exemplary embodiment, two echo signals in each group of echo signals are fused into a corresponding single-frame point cloud to obtain a target frame set, including:

[0066] S21, based on the signal difference at the same position point of two echo signals in each group of echo signals, determine the single-frame point cloud corresponding to each group of echo signals to obtain a target frame set, wherein, in the target frame set, the value of a position point corresponds to the signal difference between the two echo signal position points corresponding to the position point.

[0067] When fusing the two echo signals in each group of echo signals, a single-frame point cloud corresponding to each group of echo signals, i.e., a single-frame point cloud obtained from each detection, can be determined based on the signal difference at the same position point between the two echo signals in each group of echo signals, thereby obtaining a target frame set. Here, determining the single-frame point cloud corresponding to each group of echo signals based on the signal difference at the same position point between the two echo signals in each group of echo signals can be performed by converting the signal difference at the same position point between the two echo signals in each group of echo signals into the value of the same position point in the single-frame point cloud corresponding to each group of echo signals according to a preset conversion relationship.

[0068] Optionally, in the target frame set, the value of a location point can be used to identify the degree of dirtiness at that location point (which can be considered a dirtiness tag for that location point). The higher the dirtiness at a location point, the larger the signal value of the echo signal corresponding to that location point. Conversely, the lower the dirtiness at a location point, the smaller the signal value of the echo signal corresponding to that location point. Based on this feature, the aforementioned preset conversion relationship can be set. Here, the preset conversion relationship can be a positive correlation relationship or other conversion relationship, as long as it can accurately characterize the dirtiness of each location point.

[0069] For example, the dirty mark on the surface of the lidar shell can be obtained based on multiple lidar echoes. By combining two radar echoes, the dirty mark tag of the radar (used to identify the degree of obstruction of the corresponding position) can be obtained. For the n frames accumulated by the lidar point cloud, any point in each frame j It can be expressed as:

[0070] Where ρ is the modulus length, θ is the polar angle, is the azimuth angle, tag is the dirty label, which is used to identify the degree of occlusion of the corresponding position, 1≤j≤m.

[0071] Through this embodiment, by determining the single-frame point cloud corresponding to each group of echo signals based on the signal difference at the same position point of the two echo signals in each group of echo signals, the convenience of point cloud data determination can be improved, and the ability of point cloud data to represent environmental targets can be improved.

[0072] In an exemplary embodiment, acquiring a target frame set obtained by detecting a sensor housing surface of a target sensor through a target sensor includes:

[0073] S31, obtaining a target frame set obtained by detecting a laser radar shell surface of a multi-dimensional laser radar through a multi-dimensional laser radar, wherein the target sensor is a multi-dimensional laser radar.

[0074] In this embodiment, the target sensor may be a multi-dimensional laser radar, thereby more accurately representing the characteristics of the detected target based on the acquired multi-dimensional information. Here, the sensor housing surface of the target sensor is the laser radar housing surface of the multi-dimensional laser radar. Correspondingly, the target frame set may be acquired by acquiring a target frame set obtained by detecting the laser radar housing surface using the multi-dimensional laser radar. Optionally, the multi-dimensional laser radar is a three-dimensional laser radar.

[0075] Through this embodiment, the use of a multi-dimensional laser radar to acquire a cumulative point cloud can improve the ability of the cumulative point cloud to represent the detection target, thereby improving the accuracy of target detection.

[0076] In an exemplary embodiment, each position point in each target frame is represented by a set of position parameters, such as the aforementioned modulus, polar angle and azimuth angle, or x-coordinate, y-coordinate and z-coordinate; the value of each position point in each target frame is used to represent the degree of occlusion of the corresponding position point, which can be considered as a dirty label of the corresponding position point.

[0077] Correspondingly, before performing the projection operation on the target frame set, the method further includes:

[0078] S41 , performing a filtering operation on a target frame set based on at least one position parameter to obtain a filtered target frame set, wherein the at least one position parameter belongs to a group of position parameters.

[0079] Taking into account the installation angle and gap of the target sensor (for example, the radar installation angle and gap), dirt may be hidden on the target sensor, the surface of the sensor housing or other objects within the detectable range of the target sensor. In this regard, it is possible to consider filtering the target frame set based on all or part of the position parameters in a set of position parameters (that is, at least one position parameter). This can improve the accuracy of target detection while reducing the amount of data to be processed. Here, at least one position parameter belongs to a set of position parameters.

[0080] In this embodiment, a filtering operation can be performed on the target frame set based on at least one position parameter to obtain a filtered target frame set. Here, the position parameters used to perform the filtering operation on the target frame set can be multiple, and the filtering operation can be performed on the target frame set in sequence using the multiple position parameters. After filtering the target frame set using the last position parameter of the multiple position parameters, the filtered target frame set can be obtained. Optionally, to improve processing efficiency, the filtering operation can be performed on the target frame set separately using the multiple position parameters, and the intersection of the filtered target frame sets is determined as the filtered target frame set.

[0081] For example, as shown in FIG4 , two position parameters can be used to perform a filtering operation on a target frame set. In the case where the filtering operation is performed on the target frame set sequentially, the filtering operation performed using the latter position parameter is performed on the target frame set obtained after the filtering operation is performed on the target frame set using the previous position parameter (including unfiltered collaboration). In the case where the filtering operation is performed on the target frame set separately, after performing the filtering operation on the target frame set using each position parameter separately, two filtered target frame sets can be obtained, and the intersection of the two filtered target frame sets is determined as the final filtered target frame set.

[0082] Through this embodiment, by using at least one position parameter to perform a forward operation on a position point in the accumulated point cloud, the target detection accuracy can be improved while reducing the amount of data required for processing.

[0083] In an exemplary embodiment, performing a filtering operation on the target frame set based on at least one position parameter to obtain a filtered target frame set includes at least one of the following:

[0084] S51, filtering out the position points in the target frame set whose corresponding modulus length is not a specified value, to obtain the target frame set after modulus length filtering;

[0085] S52 , filtering out position points in the target frame set whose corresponding polar angles are greater than or equal to a specified angle, to obtain a target frame set after polar angle filtering.

[0086] In this embodiment, considering that the installation angle and gaps of the target sensor can harbor dirt, the points in the target frame set can be filtered based on at least one of modulus length and polar angle. When filtering based on modulus length, points in the target frame set whose corresponding modulus length does not exceed a specified value can be filtered out, resulting in a modulus-length-filtered target frame set. The specified value can be set based on the position of the coordinate origin of a spherical coordinate system, for example, the modulus length value corresponding to the sensor housing surface. When filtering based on polar angle, points in the target frame set whose corresponding polar angle is greater than or equal to a specified angle can be filtered out, resulting in a polar-angle-filtered target frame set. The specified angle is determined based on the installation position of the sensor housing, and the coverage area can be a range that does not include gaps at the edge of the sensor housing.

[0087] For example, in order to reduce the influence of points not on the radome, the accumulated point cloud can be filtered based on the modulus ρ. The filtered points can be those where the modulus is not 0 in the accumulated point cloud:

[0088] 1 means retain; 0 means discard.

[0089] For example, in order to reduce the influence of dirt gaps, the accumulated point cloud can be filtered based on the polar angle θ, and the filtered point cloud can be the point cloud with a polar angle exceeding the set threshold θ. thres Location point:

[0090] Among them, 1 means keep; 0 means discard; θ thres Indicates the angle of the dirty gap relative to the z-axis.

[0091] Through this embodiment, the position points in the accumulated point cloud are filtered based on at least one of the modulus and the polar angle, which can reduce the influence of points on the sensor housing and the influence of dirty gaps, and improve the convenience of position point filtering.

[0092] In one exemplary embodiment, a set of position parameters includes three axis coordinates in a rectangular coordinate system, and the position points in the target frame set acquired by the target sensor can be represented by a spherical coordinate system. In this case, the position points in the spherical coordinate system can be converted to position points in the rectangular coordinate system through coordinate transformation. The tilt angle of the target sensor includes the roll angle (in the roll direction) and the pitch angle (in the pitch direction).

[0093] In order to reduce the influence of ground points on target detection, the position points in the target frame set are filtered using the tilt angle of the target sensor. Correspondingly, a filtering operation is performed on the target frame set based on at least one position parameter to obtain a filtered target frame set, including:

[0094] S61, transforming the coordinate values ​​of the three axis coordinates of each position point in the target frame set using a first rotation matrix and a second rotation matrix to obtain a target frame set after coordinate transformation, wherein the first rotation matrix is ​​a rotation matrix determined according to the roll angle, and the second rotation matrix is ​​a rotation matrix determined according to the pitch angle;

[0095] S62 , filtering out the position points whose corresponding z-axis coordinates are smaller than a preset value in the target frame set after coordinate transformation, to obtain the target frame set after coordinate filtering.

[0096] In this embodiment, it is considered that the coordinate values ​​of the three-axis coordinates of the position points in the target frame set are the coordinate values ​​in the sensor coordinate system. To this end, it is necessary to convert the coordinate values ​​in the sensor coordinate system into the coordinate values ​​in the world coordinate system before performing point cloud filtering. The rotation matrix used to convert the coordinate values ​​in the sensor coordinate system of the target sensor into the coordinate values ​​in the world coordinate system includes a first rotation matrix and a second rotation matrix, wherein the first rotation matrix is ​​a rotation matrix determined according to the roll angle (i.e., the rotation matrix in the roll direction), and the second rotation matrix is ​​a rotation matrix determined according to the pitch angle (i.e., the rotation matrix in the pitch direction).

[0097] When performing a filtering operation on a target frame set, the first rotation matrix and the second rotation matrix can be used to first transform the axis coordinates of each position point in each target frame to obtain a target frame set after coordinate transformation. At this time, each position point in the target frame set is represented by the coordinate values ​​of the three coordinate axes in the world coordinate system; then, in the target frame set after coordinate transformation, the position points whose corresponding z-axis coordinates are less than a preset value are filtered out to obtain a target frame set after coordinate filtering. Here, the preset value is a value greater than or equal to the z-axis coordinate corresponding to the ground.

[0098] For example, in order to reduce the influence of ground points, the radar tilt angle (roll direction and pitch direction) is used for filtering: the point cloud after coordinate transformation is transformed using the rotation matrix in the roll direction and pitch direction, and filtering is performed based on the transformed point cloud. The rotation matrix in the roll direction and pitch direction is shown in formula (1) and formula (2):

[0099] Among them, R X and R Y They can be expressed as rotation matrices in the roll and pitch directions, respectively. The formula for coordinate transformation using the rotation matrices in the roll and pitch directions is shown in formula (3):

[0100] The way to filter the point cloud after coordinate transformation is:

[0101] Among them, 1 means keep, 0 means discard; rotation Represents the coordinates after rotation.

[0102] Through this embodiment, by using the rotation matrix corresponding to the roll angle and pitch angle of the sensor to transform the coordinates of the accumulated point cloud, and filtering out points whose z-axis coordinates are less than the specified value, the influence of ground points on target detection can be reduced and the accuracy of target detection can be improved.

[0103] In an exemplary embodiment, performing a projection operation on a target frame set to obtain a target projection image includes:

[0104] S71, projecting the target frame set onto a specified plane to obtain target projection information corresponding to the target frame set, wherein the target projection information is used to represent the pixel position to which each position point in the target frame set is projected and the pixel value corresponding to each position point, and the pixel value corresponding to each position point is the pixel value of each position point projected onto the specified plane;

[0105] S72: Generate a target projection image according to the pixel position to which each position point is projected and the pixel value corresponding to each position point.

[0106] When performing a projection operation on a target frame set, each position point in the target frame set can be projected into a specified plane respectively, thereby obtaining target projection information. Here, the target projection information is used to indicate the pixel position to which each position point in the target frame set is projected, and the pixel value corresponding to each position point. The pixel value corresponding to each position point is the pixel value of each position point projected into the specified plane. Here, the pixel value corresponding to each position point can be the label value of the aforementioned dirt label of each position point in the target frame set, or a value obtained by weighting the label value of the aforementioned dirt label of each position point in the target frame set, or a value determined in combination with other projection technologies, which is not limited in this embodiment.

[0107] A target projection image can be generated based on the pixel position to which each position point is projected and the pixel value corresponding to each position point. Here, the image area of ​​the target projection image can be pre-set or determined based on the pixel positions to which all position points in the target frame set are projected. The width of the final projection image can be represented by width, and the height can be represented by height.

[0108] For example, the filtered LiDAR point cloud can be projected using Polar Stereographic Projection or other projection methods to project the spherical coordinates to the plane coordinates. The projection is the LiDAR spherical coordinates dirt mark. The formula for projecting the spherical coordinates to the plane coordinates can be as follows: θ = π - θ (4)

[0109] Where radius is the projection radius; width is the width of the final projected image; and height is the height of the final projected image.

[0110] The projection position can be calculated using formula (6) and formula (7):

[0111] Where R is the polar coordinate radius after projection, θ is the polar angle after projection, and x and y are the x-axis and y-axis coordinates after projection.

[0112] According to this embodiment, by projecting each position point in the accumulated point cloud onto a designated plane and generating a projection image based on the projection information of each position point, the convenience of generating the projection image can be improved.

[0113] In an exemplary embodiment, generating a target projection image according to the pixel position to which each position point is projected includes:

[0114] S81, when there is a position point set in the target frame set that is projected to the same pixel position, determining an average value of pixel values ​​corresponding to the position points in the position point set as the pixel value of the pixel position in the target projection image to which the position point set is projected;

[0115] S82, determining pixel values ​​corresponding to other position points in the target frame set except the position points in the position point set as pixel values ​​of pixel positions to which the other position points in the target projection image are projected;

[0116] S83 , when there is a group of pixel positions whose pixel values ​​are not determined within the image area of ​​the target projection image, determine the designated pixel value as the pixel value of the group of pixel positions in the target projection image.

[0117] The target frame set may contain some points projected to the same pixel location, or some points projected to different locations. In the projected image, there may be some pixel locations where no points are projected. The pixel values ​​of these pixel locations can be determined separately for each of these different situations.

[0118] If a set of position points exists in the target frame set that projects to the same pixel position, the maximum, minimum, or median value of the pixel values ​​corresponding to the position points in the position point set may be determined as the pixel value of the pixel position in the target projection image to which the position point set projects. Optionally, to improve the ability of pixel values ​​to represent the state of the corresponding position points, the average value of the pixel values ​​corresponding to the position points in the position point set may be determined as the pixel value of the pixel position in the target projection image to which the position point set projects.

[0119] The pixel values ​​corresponding to the other position points in the target frame set, except for the position points in the position point set, are determined as the pixel values ​​of the pixel positions in the target projection image to which the other position points are projected. If there is a group of pixel positions with undetermined pixel values ​​within the image area of ​​the target projection image, the specified pixel value can be determined as the pixel value of the group of pixel positions in the target projection image. In this way, the pixel values ​​of all pixel positions in the target projection image can be determined, thereby generating the target projection image.

[0120] For example, when there are multiple point clouds projected to the same position, the mean of all positions can be calculated as the pixel value of the corresponding pixel position on the projected image, as shown in formula (8):

[0121] Among them, mean (x,y) is the mean value of dirt at the projected image position (x, y); tag iis the degree of dirtiness of the image point, and size is the number of point clouds projected to the projected image position (x, y). In addition, you can also fill in the positions where there are no point clouds projected.

[0122] Through this embodiment, by generating a target projection image according to the pixel position to which each position point is projected, the accuracy of acquiring the target projection image can be improved.

[0123] In an exemplary embodiment, the target frame set is obtained by detecting the sensor housing surface by the target sensor during one of a plurality of consecutive time intervals. The classification result corresponding to each of the plurality of consecutive time intervals is a confidence score output by the target classification model corresponding to each of a plurality of preset categories.

[0124] Correspondingly, after inputting the target projection image into the trained target classification model to obtain the target classification result, the above method further includes:

[0125] S91, smoothing multiple confidence levels corresponding to the same preset category in the classification results corresponding to each time interval to obtain a smoothed confidence level corresponding to each preset category;

[0126] S92: Determine the preset category with the highest corresponding smoothing confidence among the multiple preset categories as the target category corresponding to the multiple continuous time intervals.

[0127] In this embodiment, in order to increase the reliability of the inference results (i.e., the prediction results of the classification model), the confidence levels of the classification results corresponding to multiple consecutive time intervals can be smoothed: first, the multiple confidence levels corresponding to the same preset category in the classification results corresponding to each time interval are smoothed to obtain the smoothed confidence level corresponding to each preset category, and then, the preset category with the highest corresponding smoothed confidence level among the multiple preset categories is determined as the target category corresponding to the multiple consecutive time intervals.

[0128] For example, when using the trained model for inference deployment, you can connect to the lidar and process the lidar data in real time in a similar way to the above. Use the data after model inference to obtain the model's inference results. Considering that rain is a continuous process, it is necessary to smooth the continuous inference results within a certain time interval to increase the reliability of the inference results. Conf can be used to represent the confidence level of rain at t moments, where Conf = {conf1,conf2,…,conf t},conf t =β*conf t-1 +(1-β)θ t , β=(t-1) / t is the preset weighting coefficient, θt is the confidence that it will rain at time t, conf t is the confidence level after exponential sliding average at time t.

[0129] The confidence level of rain in a specified time interval can be smoothed using an exponential moving average, as shown in formula (9):

[0130] Where thres is the preset confidence threshold for rain.

[0131] Through this embodiment, by performing smoothing processing on multiple classification results to obtain smoothed classification results, the credibility of the model output result can be enhanced.

[0132] In an exemplary embodiment, the method further includes:

[0133] S101, performing a training sample acquisition operation multiple times based on a reference sensor to obtain a training image sample set, wherein the reference sensor and the target sensor are sensors of the same model, and labeling information of each training image sample in the training image sample set is used to indicate one of a plurality of preset categories;

[0134] S102 , performing model training on a target classification model to be trained based on each training image sample and the annotation information of each training image sample to obtain a trained target classification model.

[0135] In this embodiment, a selected sensor model (i.e., a reference sensor) can be used to acquire training samples for training a classification model: training sample acquisition operations are performed multiple times based on the reference sensor to obtain a set of training image samples. Here, the selected model refers to the model of the target sensor. Using a sensor of the same model to acquire training samples can improve the target detection performance of the trained classification model in actual scenarios. The annotation information for each training image sample is used to indicate one of multiple preset categories. The annotation can be manual, a combination of machine and manual, or other annotation methods. This embodiment does not limit the annotation method for the training image samples.

[0136] In this embodiment, the training sample acquisition operation includes: obtaining a reference frame set obtained by detecting the sensor housing surface of the reference sensor using a reference sensor, where each reference frame in the reference frame set is a single-frame point cloud obtained by a single detection by the reference sensor; and performing a projection operation on the reference frame set to obtain a training image sample. The methods for obtaining the reference frame set and performing the projection operation are similar to those in the previous embodiment and are not further described here.

[0137] Based on each training image sample and the annotation information of each training image sample, the target classification model to be trained can be trained to obtain a trained target classification model. The method of training the classification model can refer to relevant technologies and is not limited in this embodiment.

[0138] For example, as shown in Figure 5, to detect rain and non-rain scenarios using LiDAR and a deep neural network, training data can be acquired (i.e., data collection) in a similar manner as described above: A selected LiDAR model is connected and data is collected using the connected LiDAR to obtain positive and negative samples, where positive samples represent rain data and negative samples represent non-rain data. The data collection steps here include point cloud accumulation, point cloud filtering, and stereographic projection.

[0139] In addition to data collection, you can also select a model (i.e., a rain classification model), a loss function, an optimizer, and data augmentation methods: Select a model to train a rain classification model. Here, you can choose an appropriate backbone network, such as the ResNet series or the EfficientNet series. Output categories are two: rain or no rain. Use methods such as random rotation, random upside-down flipping, random left-right flipping, and random erasing to enhance the data. Select binary cross entropy as the loss function and Adam as the optimizer. Use the above configuration to train the model. For the trained model, you can evaluate its performance. If it meets the model evaluation criteria, output the model. If not, perform data analysis, supplement the data, adjust the parameters, and retrain the model.

[0140] Here, the above-mentioned lidar rain detection solution based on deep neural network can effectively perform rain detection, that is, effectively detect rain scenes such as light rain, moderate rain and heavy rain. In addition, it can also effectively detect non-rain scenes such as dust, grass clippings, and mud, as long as the data collection and output categories of the corresponding scenes are increased.

[0141] As shown in Figure 6, when deploying a rain detection application, you can first connect to the lidar to obtain radar contamination data, that is, point cloud data; accumulate, filter, and stereographically project the obtained point cloud data, then perform model inference and output the results; to enhance the credibility of the model output results, synthesize multiple inference results and output the final result.

[0142] Through this embodiment, a sensor of a specified model is used to collect training image samples, and the obtained training image samples are used to train the classification model, which can improve the target detection effect of the trained classification model in actual scenarios.

[0143] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0144] According to another aspect of the embodiments of the present application, a target detection device for a lawn mower is also provided. The device is used to implement the target detection method for a lawn mower provided in the above-mentioned embodiments. The details that have been described will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0145] FIG7 is a block diagram of a target detection device for a lawn mower according to an embodiment of the present application. As shown in FIG7 , the device includes:

[0146] an acquisition unit 702 configured to acquire a target frame set obtained by detecting a sensor housing surface of a target sensor using a target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by a single detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating the point cloud;

[0147] The first execution unit 704 is configured to perform a projection operation on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane;

[0148] The input unit 706 is used to input the target projection image into the trained target classification model to obtain a target classification result, wherein the target classification model is a classification model used to distinguish multiple preset categories, and the target classification result is used to indicate the preset category that matches the target frame set among the multiple preset categories.

[0149] Through the embodiments of the present application, a target frame set is obtained by detecting the sensor shell surface of the target sensor through the target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by a detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; a projection operation is performed on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; the target projection image is input into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model for distinguishing multiple preset categories, and the target classification result is used to indicate a preset category among multiple preset categories that matches the target frame set, thereby solving the problem of the target detection method in the related art that the device is too large and the device design is difficult.

[0150] In an exemplary embodiment, the acquiring unit includes:

[0151] A first acquisition module is configured to acquire multiple groups of echo signals obtained by transmitting a detection signal multiple times by the target sensor to the surface of the sensor housing, wherein each group of echo signals in the multiple groups of echo signals includes two echo signals corresponding to a single detection signal transmitted;

[0152] The fusion module is configured to fuse the two echo signals in each group of echo signals into a corresponding single-frame point cloud to obtain a target frame set.

[0153] In an exemplary embodiment, one echo signal in each group of echo signals is an echo signal reflected by the surface of the sensor housing, and the other echo signal is an echo signal reflected by the detected target.

[0154] In an exemplary embodiment, the fusion module includes:

[0155] The first determination subunit is configured to determine a single-frame point cloud corresponding to each group of echo signals based on the signal difference at the same position point of two echo signals in each group of echo signals, and obtain a target frame set, wherein in the target frame set, the value of a position point corresponds to the signal difference between the two echo signal position points corresponding to the position point.

[0156] In an exemplary embodiment, each position point in each target frame is represented by a set of position parameters, and the value of each position point in each target frame is used to represent the degree of occlusion of the corresponding position point;

[0157] The above device also includes:

[0158] The second execution unit is configured to perform a filtering operation on the target frame set based on at least one position parameter to obtain a filtered target frame set, wherein the at least one position parameter belongs to a group of position parameters.

[0159] In an exemplary embodiment, the second execution unit includes at least one of the following:

[0160] The first filtering module is configured to filter out the position points in the target frame set whose corresponding modulus length is not a specified value, thereby obtaining the target frame set after modulus length filtering;

[0161] The second filtering module is configured to filter out position points in the target frame set whose corresponding polar angles are greater than or equal to a specified angle, to obtain a target frame set after polar angle filtering.

[0162] In an exemplary embodiment, a set of position parameters includes three axis coordinates in a rectangular coordinate system; the tilt angle of the target sensor includes a roll angle and a pitch angle;

[0163] The second execution unit includes:

[0164] a transformation module configured to transform the coordinate values ​​of the three axis coordinates of each position point in the target frame set using a first rotation matrix and a second rotation matrix to obtain a target frame set after coordinate transformation, wherein the first rotation matrix is ​​a rotation matrix determined according to the roll angle, and the second rotation matrix is ​​a rotation matrix determined according to the pitch angle;

[0165] The third filtering module is configured to filter out position points whose corresponding z-axis coordinates are less than a preset value in the target frame set after coordinate transformation, to obtain the target frame set after coordinate filtering.

[0166] In an exemplary embodiment, the first execution unit includes:

[0167] a projection module configured to project the target frame set into a specified plane to obtain target projection information corresponding to the target frame set, wherein the target projection information is used to represent a pixel position to which each position point in the target frame set is projected and a pixel value corresponding to each position point, and the pixel value corresponding to each position point is a pixel value of each position point projected into a pixel point in the specified plane;

[0168] The generation module is configured to generate a target projection image according to the pixel position to which each position point is projected and the pixel value corresponding to each position point.

[0169] In an exemplary embodiment, the generation module includes:

[0170] The second determining subunit is configured to, when there is a position point set projected to the same pixel position in the target frame set, determine an average value of pixel values ​​corresponding to the position points in the position point set as the pixel value of the pixel position projected to the position point set in the target projection image;

[0171] a third determining subunit configured to determine pixel values ​​corresponding to other position points in the target frame set except for the position points in the position point set as pixel values ​​of pixel positions to which the other position points in the target projection image are projected;

[0172] The fourth determining subunit is configured to determine the designated pixel value as the pixel value of a group of pixel positions in the target projection image when there is a group of pixel positions with undetermined pixel values ​​in the image area of ​​the target projection image.

[0173] In an exemplary embodiment, the target frame set is obtained by detecting the sensor housing surface by the target sensor in one of a plurality of continuous time intervals; the classification result corresponding to each of the plurality of continuous time intervals is a confidence level output by the target classification model and corresponding to each of a plurality of preset categories;

[0174] The above device also includes:

[0175] a processing unit configured to perform smoothing processing on a plurality of confidence levels corresponding to the same preset category in the classification results corresponding to each time interval to obtain a smoothed confidence level corresponding to each preset category;

[0176] The determining unit is configured to determine, among the plurality of preset categories, a preset category corresponding to the highest smoothing confidence as a target category corresponding to the plurality of continuous time intervals.

[0177] In an exemplary embodiment, the apparatus further comprises:

[0178] an acquisition unit configured to perform a training sample acquisition operation multiple times based on a reference sensor to obtain a training image sample set, wherein the reference sensor and the target sensor are sensors of the same model, and labeling information of each training image sample in the training image sample set is used to indicate one of a plurality of preset categories;

[0179] A training unit is configured to perform model training on a target classification model to be trained based on each training image sample and the annotation information of each training image sample to obtain a trained target classification model;

[0180] The training sample collection operation includes:

[0181] Acquire a reference frame set obtained by detecting a sensor housing surface of the reference sensor using the reference sensor, wherein each reference frame in the reference frame set is a single-frame point cloud obtained by performing one detection by the reference sensor;

[0182] Perform a projection operation on the reference frame set to obtain a training image sample.

[0183] In an exemplary embodiment, the acquiring unit includes:

[0184] The second acquisition module is configured to acquire a target frame set obtained by detecting the laser radar shell surface of the multi-dimensional laser radar through a multi-dimensional laser radar, wherein the target sensor is a multi-dimensional laser radar.

[0185] In an exemplary embodiment, the multi-dimensional lidar is a three-dimensional lidar.

[0186] In an exemplary embodiment, the target sensor is an integrated sensing device, and the target sensor is also used for at least one of the following: navigation, positioning, and obstacle avoidance.

[0187] In an exemplary embodiment, the plurality of preset categories are used to represent at least one of the following targets: rain, hail, snow, sandstorm, and fog.

[0188] In an exemplary embodiment, the target sensor is used for rain detection, navigation, positioning, and obstacle avoidance.

[0189] In an exemplary embodiment, the sensor housing surface is planar and / or curved.

[0190] In one exemplary embodiment, the target sensor is positioned at an angle to the horizontal at a front region of the top of the lawn mower.

[0191] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0192] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is configured to execute the steps of any of the above method embodiments when run.

[0193] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0194] According to one aspect of the present application, a computer program product is provided, comprising a computer program / instruction containing program code for executing the method shown in the flowchart. In such an embodiment, referring to FIG8 , the computer program can be downloaded and installed from a network via a communication portion 809 and / or installed from a removable medium 811. When the computer program is executed by a central processing unit 801, the various functions provided by the embodiments of the present application are performed. The serial numbers of the embodiments of the present application are for description only and do not represent the merits or demerits of the embodiments.

[0195] Refer to FIG8 , which is a structural block diagram of a computer system of an optional electronic device according to an embodiment of the present application.

[0196] Figure 8 schematically shows a computer system structure block diagram for implementing the electronic equipment of the embodiment of the present application. As shown in Figure 8, computer system 800 includes a central processing unit 801 (Central Processing Unit, referred to as CPU), which can perform various appropriate actions and processes according to the program stored in the read-only memory 802 (Read-Only Memory, ROM) or the program loaded from the storage part 808 into the random access memory 803 (Random Access Memory, referred to as RAM). In the random access memory 803, various programs and data required for system operation are also stored. The central processing unit 801, the read-only memory 802 and the random access memory 803 are connected to each other through a bus 804. An input / output interface 805 (Input / Output interface, referred to as I / O interface) is also connected to the bus 804.

[0197] The following components are connected to the input / output interface 805: an input section 806 including a keyboard, a mouse, and the like; an output section 807 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 808 including a hard disk; and a communication section 809 including a network interface card such as a local area network card or a modem. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output interface 805 as needed. Removable media 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like, is installed in the drive 810 as needed, so that computer programs read therefrom can be installed into the storage section 808 as needed.

[0198] In particular, according to an embodiment of the present application, the processes described in the various method flow charts can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the methods shown in the flow charts. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 809 and / or installed from a removable medium 811. When the computer program is executed by the central processing unit 801, the various functions defined in the system of the present application are performed.

[0199] It should be noted that the computer system 800 of the electronic device shown in FIG8 is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0200] According to another aspect of the embodiments of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.

[0201] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0202] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail here.

[0203] According to another aspect of the embodiment of the present application, a lawn mower control method is also provided. The method embodiment provided in the embodiment of the present application can be executed in a lawn mower (as shown in Figure 1) or a similar processing device. It has been explained and will not be repeated here.

[0204] The lawn mower control method provided in this embodiment can be executed by the lawn mower alone, or by a user terminal (a terminal device, which can be a mobile terminal, an integrated terminal, etc.) or a base station and the lawn mower together. Taking the lawn mower control method of this embodiment as an example, as shown in Figure 9, the process of the lawn mower control method can include the following steps:

[0205] S902, when there is water stain on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once, and determining the current weather based on the obtained water signal;

[0206] S904, controlling the lawn mower to perform corresponding actions according to the current weather; including: when it is determined that the current weather is bad weather, performing a shielding action on at least part of the lawn mower.

[0207] Similar to the aforementioned embodiment, the lawn mower control method in this embodiment can be applied to a scenario where target detection is performed on a lawn mower or similar equipment. The lawn mower can be provided with at least one laser radar, which can detect the environment in which the lawn mower is located by using the provided laser radar to determine whether a water signal on the shell surface is detected. During the operation of the lawn mower (the lawn mower can be in working state or idle state, can be in moving state or stationary state, as long as it can power the laser radar and parse the acquired laser radar data), the laser radar can detect the shell surface and obtain the laser radar data; by parsing the laser radar data, the water signal on the above-mentioned shell surface can be obtained.

[0208] It should be noted that the method of detecting the shell surface by laser radar is similar to the method of detecting the sensor shell surface by the target sensor in the aforementioned embodiment. In this case, the target sensor may include a laser radar, and correspondingly, the sensor shell surface of the target sensor may include the shell surface of the laser radar. Optionally, other methods can be used to detect the shell surface by laser radar to obtain a corresponding water signal. The water signal can be represented by a set of specified parameters. The above set of specified parameters can be used to indicate whether there is water stain on the shell surface of the laser radar and the state of the water stain, which may include but is not limited to at least one of the following: the shape of the water, the area covered by the water, the position of the water coverage, etc., and may also include other parameters that can characterize the water stain on the shell surface.

[0209] In this embodiment, the lawn mower can detect the environment in which the lawn mower is located by at least one laser radar, thereby determining the current weather. Here, at least one laser radar can be set at any position on the lawn mower that can detect the environmental status, for example, the front, side, rear, etc. Different laser radars can be set at different positions, and the detection areas of different laser radars can at least partially overlap or not completely overlap, which is not limited in this embodiment. A method for detecting severe weather by laser radar can be: parsing the point cloud data detected by the laser radar and performing severe weather detection based on the parsed objects.

[0210] Optionally, the lawn mower may be further provided with a control module, for example, a first control module, and the lawn mower control method in this embodiment may be executed by this control module. The control module may acquire a water signal obtained by a laser radar detecting the shell surface. This acquisition operation may be implemented by acquiring laser radar data detected by the laser radar, parsing the acquired laser radar data, and obtaining a corresponding water signal, thereby acquiring the water signal obtained by the laser radar detecting the shell surface.

[0211] Optionally, the control module can obtain laser radar data through the laser radar, and then obtain the status of the shell surface of the laser radar (that is, whether there are water stains on the shell surface of the laser radar). When water stains are detected on the shell surface, the current weather is determined based on the water signal obtained on the shell surface of the laser radar. The control module obtains the laser radar to detect the water signal on the shell surface, which can be performed periodically or triggered by an event. If there are no water stains on the shell surface of the laser radar, the control module may not obtain the water signal. If there are water stains on the shell surface of the laser radar, the water signal obtained by the laser radar detecting its shell surface can be obtained; based on the obtained water signal, the current weather can be determined.

[0212] The determination of the current weather can be based on a water signal acquired once or based on multiple water signals acquired. Therefore, if there is water on the shell surface of the laser radar, the control module can obtain the water signal obtained by the laser radar detecting the shell surface at least once, and determine the current weather based on the obtained water signal. The current weather can be determined by determining the type of weather (for example, rain, hail, snow, sunny, etc.) or by determining whether the current weather is a specified weather (for example, rain).

[0213] The lawn mower can be controlled to perform corresponding actions based on the current weather. For example, if the current weather is sunny, the lawn mower can be controlled to continue mowing. For another example, if the current weather is raining, the lawn mower can be controlled to pause mowing. For another example, if the current weather is raining, the lawn mower can be controlled to continue mowing, return to the base station or a designated location based on the intensity of the rain, etc. The actions corresponding to different weather conditions can be pre-set or adjusted according to user needs.

[0214] In this embodiment, if the current weather is determined to be inclement, a shielding action is performed on at least a portion of the lawn mower. Shielding the lawn mower is performed to protect the laser radar or the entire lawn mower from the harsh external environment. Specifically, the above-mentioned actions may include: controlling the lawn mower to return to a base station that matches the lawn mower, controlling the lawn mower to move to a designated location, and controlling a shielding member to shield at least a portion of the lawn mower (the laser radar, the body of the lawn mower, etc.) so that the lawn mower is at least partially shielded. The main working parts of a lawn mower include a cutter disc, a laser radar, and a drive wheel. Continuous operation in inclement weather (such as rain) can cause the cutter disc to rust, the laser radar to become flooded, and the drive wheel to become stuck in mud, thereby reducing the service life of the lawn mower.

[0215] When the main body of the laser radar is exposed to the external environment, it helps to detect weather conditions more accurately. However, when the main body of the laser radar is exposed to the external environment, its rainproof performance will be affected, and the waterproof level of the laser radar installation components needs to be improved. The lawn mower just needs a non-rainy working environment. Such conditions just meet the requirements for installing the laser radar on the lawn mower to detect bad weather, without the need for additional sealing structures to improve the waterproof level of the laser radar, thereby reducing the manufacturing cost of the entire machine.

[0216] In this embodiment, determining the current weather requires a certain amount of time, and weather changes also require a certain amount of time. To ensure mowing efficiency, the lawn mower can be controlled to continue mowing according to a pre-set cutting path and cutting pattern before the current weather is determined. Optionally, to improve the accuracy and timeliness of weather determination, the lawn mower can obtain weather information corresponding to the location of the lawn mower and determine the current weather based on the obtained weather information, or determine the current weather based on the obtained weather information and the obtained water signal. There are various ways to obtain weather information corresponding to the location of the lawn mower, such as directly obtaining weather information corresponding to the location of the lawn mower from the network (in this case, the lawn mower has network connectivity), or obtaining weather information corresponding to the location of the lawn mower from a terminal device associated with the lawn mower. This embodiment does not limit the method for obtaining weather information corresponding to the location of the lawn mower.

[0217] Through the above steps, when there are water stains on the shell surface of the laser radar, a water signal obtained by the laser radar detecting the shell surface at least once is obtained, and the current weather is determined based on the obtained water signal; the lawn mower is controlled to perform corresponding actions according to the current weather; including: when it is determined that the current weather is bad weather, a shielding action is performed on at least part of the lawn mower, which can reduce the impact of weather factors on the operation of the lawn mower, ensure the safety of the lawn mower, and increase the service life of the lawn mower.

[0218] Before determining the current weather, the mower continues mowing according to the pre-set cutting path and cutting pattern. This setting is for two reasons: First, the lidar has a short detection cycle for rain, and in most cases, it can output a judgment result within 30 seconds. In general, heavy rain will output a judgment result faster than light rain. Therefore, before determining the current weather, the mower continues mowing according to the established pattern and route. This will not affect the performance of the mower due to rain, but will avoid the continuous starting and stopping of the travel motor and cutting motor, ensuring the service life of the motors while not affecting the working efficiency of the mower. On the other hand, if the mower stops moving and cutting before determining the current weather, and the mower remains in place to continue determining the current weather, if the mower happens to be in the location where it stops due to artificial precipitation (for example, a high diversion pipe or a high water container dumped), this will cause the lidar to continuously obtain water signals, resulting in a misjudgment of the weather, or even cause the mower to get stuck in mud, leading to adverse consequences. In short, before determining the current weather, the lawn mower continues to mow according to the established route and pattern, which can ensure the safety of the lawn mower, increase the service life of the lawn mower, and at the same time ensure the mowing efficiency of the lawn mower.

[0219] In an exemplary embodiment, when the current weather is judged to be severe weather, shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be severe weather, controlling the lawn mower to return to a base station matched with the lawn mower.

[0220] In this embodiment, if the current weather is determined to be inclement, the lawn mower can be controlled to return to a base station that matches the mower to prevent damage. Typically, base stations are located in sheltered spaces, such as indoors, to protect them from environmental factors such as sunlight, rain, wind, and snow, which could cause short circuits, corrosion, and dust accumulation, thereby shortening the mower's service life. Furthermore, the matching relationship between the base station and the mower can be pre-set, eliminating the need for algorithms to select the appropriate parking location, thereby improving the timeliness of mower control.

[0221] Here, inclement weather refers to weather that may affect the operation of the lawn mower, such as heavy snow, freezing, low temperatures, strong winds, high temperatures, heavy rainfall, and continuous rainfall. Inclement weather can be a custom configuration item (i.e., inclement weather can be weather specified through configuration information), which can correspond to a detected specified object or an object parameter of a detected specified object (e.g., quantity, area, frequency, etc.). That is, when a specified object is detected or the object parameter of a detected specified object meets the set detection conditions, the current weather is determined to be inclement weather. Other weather determination methods can also be used. Exemplarily, inclement weather includes at least one of rain, hail, snow, and fog. Here, by limiting the inclement weather to be detected, inclement weather that may affect the operation of the lawn mower can be detected, thereby improving the rationality of lawn mower operation control.

[0222] Optionally, the base station that controls the lawn mower to return can be pre-set, or it can be a corresponding base station selected from the area map (which can be the area address set on the lawn mower) according to the set selection rules after determining that the current weather is bad weather. The lawn mower can be charged and set up through this base station. At the same time, the base station can also provide a shielding function for the lawn mower.

[0223] Through this embodiment, when it is determined that the current weather is bad weather, the lawn mower is controlled to return to the base station that matches the lawn mower, which can improve the safety of the lawn mower's operation. At the same time, after the lawn mower returns to the base station, the lawn mower can be charged and maintained, so that the lawn mower can be better put into the next stage of work.

[0224] In one exemplary embodiment, when the current weather is determined to be inclement, shielding at least a portion of the lawn mower includes controlling the lawn mower to move to a designated location such that at least a portion of the lawn mower is shielded. The designated location in this embodiment can be under the eaves of a building, under an awning, or any other sheltered location. After the lawn mower reaches the designated location, it can continue mowing at the designated location or stop and park.

[0225] In this embodiment, if the current weather is determined to be inclement, the lawn mower can be controlled to move to a designated location to prevent damage to the lawn mower caused by the inclement weather. Typically, the designated location is set to a location that will not be affected by inclement weather, such as a sheltered indoor location, or a location in an area without rain or hail. The above-mentioned designated location can be pre-designated, such as a designated location under an awning, or it can be selected from an area map (which can be an area address set on the lawn mower) according to a set selection rule after the current weather is determined to be inclement. The designated location can be selected from a specified set of candidate locations, or it can be calculated in real time according to a selection algorithm, which is not limited in this embodiment.

[0226] Through this embodiment, when it is determined that the current weather is inclement, the lawn mower is controlled to move to a designated location, so that the lawn mower can be moved to a sheltered position along the shortest walking path, thereby improving the safety of the lawn mower's operation and increasing the service life of the lawn mower.

[0227] In an exemplary embodiment, when the current weather is judged to be inclement weather, a shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be inclement weather, controlling a shielding member to shield the laser radar, and the shielding member can be set on the lawn mower or outside the lawn mower. When the shielding member is set on the lawn mower, a control unit can be used to control the shielding member to shield the laser radar under inclement weather conditions, and retract under non-inclement weather conditions to expose the laser radar so that the lawn mower can operate normally; when the shielding member is set outside the lawn mower, a control unit can be used to control the shielding member to move to the position of the laser radar under inclement weather conditions to form a shield for the laser radar, and move away from the laser radar under non-inclement weather conditions to remove the shielding for the laser radar.

[0228] In an exemplary embodiment, when the current weather is judged to be inclement weather, a shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be inclement weather, controlling a shielding member to shield the body of the laser radar, the shielding member can be set on the lawn mower or can be set outside the lawn mower. When the shielding member is set on the lawn mower, a control unit can be used to deploy the shielding member to form a shield for the laser radar or retract the shielding member to remove the shielding for the laser radar; when the shielding member is set outside the lawn mower, the shielding member can be a movable canopy. When the current weather is judged to be inclement weather, the canopy can be moved to the outside of the lawn mower to form a shield for the lawn mower. When the current weather is judged to be not inclement weather, the canopy can be removed from the lawn mower, allowing the lawn mower to operate normally.

[0229] In an exemplary embodiment, the method further includes: if it is determined that the current weather is bad weather, the lawn mower may be controlled to stop mowing, wherein the cutting assembly of the lawn mower is lifted after the mowing is stopped.

[0230] The lawn mower also includes a cutting assembly for performing mowing operations. This assembly may be located at the front of the mower. The cutting assembly may include a blade or other cutting component capable of cutting. When the mower is operating, the cutting assembly may extend outward for a certain distance, and after the operation is completed, the cutting assembly may retract a certain distance. The cutting component may move vertically up and down to improve the ability to cut targets at different heights, while also preventing obstructions or unnecessary collisions caused by the low position of the target when not being cut. For example, the cutting assembly may be a cutter disc.

[0231] If the current weather is determined to be inclement, if the cutting assembly continues to mow, it may cut grass that is wet with rain, fog, snow, etc., which may not only damage the cutting assembly, but also increase the weight of the collected grass if the lawn mower has a collection function, making it difficult to clean. To address this issue, the lawn mower can be controlled to stop mowing when the current weather is determined to be inclement. Here, controlling the lawn mower to stop mowing can include controlling the cutting assembly to stop working. The method of controlling the cutting assembly to stop working can be achieved by controlling the cutting assembly to stop rotating, stopping power to the mowing assembly, etc.

[0232] Optionally, it may take some time for the cutting assembly to stop working. For example, it may take some time for the cutting assembly to stop from high speed. To prevent the cutting assembly from being damaged (e.g., a circuit burnout) due to sudden stopping, a certain resistance may be added to increase the speed at which the cutting assembly stops. However, the resistance should not be too large. To ensure the safe operation of the cutting assembly, the cutting assembly may be controlled to be raised when it is determined that the current weather is inclement. Accordingly, the cutting assembly of the lawn mower is raised after stopping mowing. Raising the cutting assembly not only improves the convenience of moving the lawn mower, but also prevents the cutting assembly from being damaged due to insufficient cutting force when cutting grass soaked with rain, fog, snow, etc. before the cutting assembly stops working.

[0233] Through this embodiment, when it is determined that the current weather is bad weather, the lawn mower can be controlled to stop mowing. After stopping mowing, the cutting component of the lawn mower is lifted up, which can reduce the risk of damage to the cutting component, improve the convenience of moving the lawn mower, and thus increase the service life of the cutting component.

[0234] In an exemplary embodiment, controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is determined that the current weather is not severe weather, controlling the lawn mower to continue mowing according to a preset cutting path and cutting mode.

[0235] Similar to the previous embodiment, the lawn mower control method of this embodiment can be applied to scenarios where target detection is performed on a lawn mower or similar device. The lawn mower may include a laser radar. The number and location of the laser radars, the characterization parameters of the water signal, and the manner in which the lawn mower obtains the water signal from the shell surface detected by the laser radar are similar to those in the previous embodiment and are not described in detail here. During the operation of the lawn mower, the laser radar can detect the shell surface and obtain laser radar data; by parsing the laser radar data, the water signal on the shell surface can be obtained.

[0236] Similar to the aforementioned embodiment, when there are water stains on the shell surface of the laser radar, a water signal obtained by the laser radar detecting the shell surface at least once can be obtained, and the current weather can be determined based on the obtained water signal. Here, taking into account the different determination methods adopted, the current weather can be determined based on the water signal obtained by the laser radar detecting the shell surface once, or based on the water signal obtained by the laser radar detecting the shell surface once; according to the current weather, the lawn mower can be controlled to perform corresponding actions, such as returning to a specified location, returning to a base station matched with the lawn mower, continuing mowing, etc., which have been explained and will not be repeated here.

[0237] In this embodiment, controlling the lawn mower to perform a corresponding action based on the current weather may include: if the current weather is determined not to be inclement weather, controlling the lawn mower to continue mowing according to a pre-set cutting path and cutting pattern. The method for controlling the lawn mower to continue mowing is similar to that described in the previous embodiment and will not be repeated here. Exemplarily, inclement weather includes at least one of rain, hail, snow, and fog.

[0238] Through the above steps, when there are water stains on the shell surface of the laser radar, a water signal obtained by the laser radar detecting the shell surface at least once is obtained, the current weather is judged based on the obtained water signal, and the lawn mower is controlled to perform corresponding actions according to the current weather; the lawn mower is controlled to perform corresponding actions according to the current weather, including: when it is determined that the current weather is not bad weather, the lawn mower is controlled to continue mowing according to a pre-set cutting path and cutting mode, which can avoid affecting the working process of the lawn mower and ensure the mowing efficiency of the lawn mower.

[0239] Specifically, the use of LiDAR for weather detection in this embodiment has a lower probability of misjudgment than using a rain sensor for weather detection. For example, when a user pours a cup of water on the rain sensor, the resistivity of the rain sensor changes, generating an electrical signal. Based on the generation of the electrical signal, non-bad weather is judged as bad weather, thereby controlling the lawn mower to return to the base station or the designated location. The use of LiDAR can avoid the occurrence of the above-mentioned misjudgment. Similarly, if a user pours a cup of water on the surface of the LiDAR, the distribution characteristics of the water signal formed by pouring a cup of water on the surface of the LiDAR are different from the distribution characteristics of the water signal formed by rain on the surface of the LiDAR. The LiDAR can distinguish between the two and therefore will not judge such a situation as bad weather. In this case, the lawn mower will not return to the base station or the designated location, but will continue mowing according to the pre-set cutting path and cutting mode.

[0240] In an exemplary embodiment, when there are water stains on the shell surface of a laser radar, a water signal obtained by the laser radar detecting the shell surface at least once is obtained, and the current weather is judged based on the obtained water signal, including: obtaining a target frame set of water signals obtained by the laser radar detecting the shell surface at least once, processing the target frame set and comparing it with a preset classification model, and judging the current weather according to the target classification result, wherein the preset classification model is classified according to different types of weather.

[0241] In this embodiment, in order to determine the current weather, the lawn mower can collect and store enough signals from the surface of the laser radar shell in different scenarios (for example, under trees, under eaves, etc.) and in bad weather in different regions (for example, rainy weather). After training, a classification model is obtained. The trained classification model can identify bad weather and non-bad weather based on the target frame set of the detected water signal. The training process of the classification model can be similar to that in the aforementioned embodiment, and has been explained, so it will not be repeated here. Correspondingly, the above-mentioned classification model can be pre-configured on the lawn mower (or it can be a server or other device), that is, a preset classification model, which can be used to determine the current weather.

[0242] A target frame set of water signals obtained by the laser radar performing at least one detection on the shell surface can be obtained. Here, each target frame in the target frame set is a single-frame point cloud obtained by the laser radar performing one detection. The target frame set can include a point cloud set obtained by the laser radar performing multiple detections on the shell surface within a certain period of time. The detection cycle of the laser radar for detecting the shell surface can be pre-configured, and the multiple detections can be continuous multiple detections or non-continuous multiple detections. The process of obtaining the target frame set is similar to that in the aforementioned embodiment and will not be repeated here.

[0243] Optionally, to facilitate the use of the preset classification model, the target frame set can be preprocessed. For example, a projection operation can be performed on the target frame set to obtain a target projection image. The process of performing the projection operation on the target frame set is similar to that in the aforementioned embodiment and is not further described here. The processed target frame set can be compared with the preset classification model, and the current weather can be determined based on the target classification result.

[0244] The weather category of the preset classification model can be a specific weather category, such as sunny, rainy, snowy, etc., or can be inclement weather or non-inclement weather. The method for comparing the processed target frame set with the preset classification model can be: input the target projection image into the preset classification model for comparison. The comparison can be performed between the target projection image and preset projection images corresponding to different weather categories or other features to determine the weather category corresponding to the target frame set, that is, the weather category indicated by the target classification result. The process of inputting the target projection image into the preset classification model to obtain the classification result is similar to that in the aforementioned embodiment and will not be described in detail here.

[0245] Through this embodiment, by obtaining a target frame set of water signals obtained by at least one detection of the shell surface by a laser radar, the target frame set is processed and compared with a preset classification model, and the current weather is judged according to the target classification result, the accuracy and reliability of the current weather judgment can be improved.

[0246] In an exemplary embodiment, a target frame set of water signals obtained by at least one detection of the shell surface by a laser radar is obtained, the target frame set is processed and compared with a preset classification model, and the current weather is judged according to the target classification result, including: performing J detections on the shell surface of the laser radar within a detection cycle, if the judgment results of the first K detections in the J detections are all that the current weather is bad weather, then the final weather is output as bad weather; if the judgment results of the first L detections in the J detections are all that the current weather is bad weather, and the judgment result of the L+1th detection is that the current weather is not bad weather, then the next detection cycle is entered until the current weather is determined; if at least one detection result in the judgment results of the first L detections in the J detections is that the current weather is not bad weather, then the final current weather is output as not bad weather, wherein L<K≤J and J≥2.

[0247] In order to reduce the error in judging the current weather, the shell surface of the laser radar can be detected J times (J ≥ 2) in one detection cycle, and the current weather can be judged based on the results of different detections. Optionally, in this embodiment, the method of judging the current weather based on the results of J detections can be:

[0248] If the first K detection results in the J detections all indicate that the current weather is bad weather, then the final weather output is bad weather. For example, within one cycle, the shell surface is detected three times, and the detection result of rain is marked as 1, and the detection result of non-rain is marked as 0. When the three output results are 111, it is determined to be rainy weather;

[0249] If the first L detection results in the J detections are all that the current weather is bad weather, and the result of the L+1th detection is that the current weather is not bad weather, then the next detection cycle is entered until the current weather is determined. For example, when the results of the three outputs are 110, the next cycle is entered;

[0250] If at least one of the judgment results of the first L detections in the J detections shows that the current weather is not bad weather, then the final output weather is not bad weather. For example, when the results of the three outputs are 100 or 000, it is determined that it is not raining.

[0251] Here, L<K≤J. The above judgment process can be understood as follows: if the judgment results of multiple consecutive tests are that the current weather is rainy, then it is judged to be rainy; if the judgment results of the previous few tests are that the current weather is rainy, and the judgment result of the last test is that the current weather is not rainy, then the current weather cannot be accurately judged (the judgment result of the last test is that it is not rainy), and it is necessary to enter the next cycle and continue to judge; and if the judgment results of the first L tests show that the current weather is not bad weather, and the judgment result of the L+1th test is that the current weather is not bad weather (that is, the judgment results of multiple tests are that the current weather is not rainy, and the judgment result of the last test is that the current weather is not bad weather), then it can be judged that the current weather is not bad weather.

[0252] Through this embodiment, the shell surface of the laser radar is detected multiple times within one detection cycle, and the current weather is comprehensively determined based on the judgment results of the multiple detections, which can improve the accuracy and reliability of the current weather judgment.

[0253] In an exemplary embodiment, the number of detections within a detection cycle can be pre-set or adjusted according to user needs. In order to improve the timeliness of the current weather judgment and at the same time improve the accuracy of the current weather judgment, the set number of detections should not be too many or too few. The appropriate number of detections can be predicted based on simulation data or actual experimental data.

[0254] Optionally, in this embodiment, J=3, K=3, L=2 can be set, that is, the shell surface of the laser radar is detected three times within one detection cycle. If the judgment results of the three detections are all that the current weather is bad weather, then the final output is that the current weather is bad weather; if the judgment results of the first two detections in the three detections are all that the current weather is bad weather, and the judgment result of the third detection is that the current weather is not bad weather, then enter the next detection cycle until the current weather is determined; if the judgment results of the first two detections in the three detections are that the current weather is not bad weather, and the judgment result of the last detection is that the current weather is not bad weather, then the final output is that the current weather is not bad weather.

[0255] Through this embodiment, by setting an appropriate number of detection times within a cycle, the timeliness and accuracy of current weather determination can be improved.

[0256] In one exemplary embodiment, the duration of a detection cycle is negatively correlated with the temperature of the shell surface. Considering that the surface temperature of the lidar shell surface affects the evaporation rate of water (i.e., in a high temperature environment, the evaporation rate of water is accelerated; in a low temperature environment, the evaporation rate of water is slowed), the duration of a detection cycle can be set based on the shell surface temperature, wherein the duration of a detection cycle is negatively correlated with the shell surface temperature.

[0257] Through this embodiment, the duration of a detection cycle is set according to the temperature of the shell surface, which can improve the efficiency of the current weather determination while ensuring the accuracy of the current weather determination.

[0258] In an exemplary embodiment, the correspondence between the temperature of the shell surface and the duration of a set detection cycle can be preset, and the above correspondence can be predicted based on simulation data or actual experimental data.

[0259] In this embodiment, the duration of the detection cycle can be set directly, or the duration of the detection cycle can be obtained based on the correspondence between the temperature of the shell surface and the duration of a detection cycle. Considering that the duration of the detection cycle should not be too long (too long will result in untimely determination of the current weather) nor too short (too short will result in inaccurate determination of the current weather), a value range of the duration of a detection cycle can be set. For example, the duration of a detection cycle is 10-30S, that is, the duration of the detection cycle directly set is within 10-30S, and the duration of the detection cycle allowed by the temperature of the shell surface is within 10-30S.

[0260] Through this embodiment, by setting a value range for the duration of a detection cycle, the efficiency of the current weather determination can be improved while ensuring the accuracy of the current weather determination.

[0261] According to another aspect of the embodiment of the present application, a lawn mower control method is also provided. The method embodiment provided in the embodiment of the present application can be executed in a lawn mower (as shown in Figure 1) or a similar processing device. It has been explained and will not be repeated here.

[0262] The lawn mower control method provided in this embodiment can be executed by the lawn mower alone, or by the user terminal or the base station and the lawn mower together. Taking the lawn mower as an example, as shown in FIG10 , the process of the lawn mower control method includes the following steps:

[0263] S1002, when there is water stain on the shell surface of the laser radar, obtaining water signals obtained by detecting the shell surface by the laser radar at least twice within a set total time period, and determining the current weather based on the obtained water signals;

[0264] S1004, controlling the lawn mower to perform corresponding actions according to the current weather; including: when it is determined that the current weather is bad weather, performing a shielding action on at least part of the lawn mower.

[0265] Similar to the aforementioned embodiment, the lawn mower control method in this embodiment can be applied to the scenario of target detection for a lawn mower or similar equipment. The lawn mower may include a laser radar. The number and setting position of the laser radar, the characterization parameters of the water signal, and the way in which the lawn mower obtains the laser radar to detect the shell surface and obtain the water signal are similar to those in the aforementioned embodiment and will not be repeated here. During the operation of the lawn mower (the lawn mower can be in working state or idle state, can be in moving state or stationary state, as long as it can power the laser radar and parse the acquired laser radar data), the laser radar can detect its shell surface and obtain the laser radar data; by parsing the laser radar data, the water signal on the above-mentioned shell surface can be obtained.

[0266] Optionally, to ensure the accuracy of current weather detection, the current weather can be determined based on changes in multiple acquired water signals. In this embodiment, if water stains are present on the shell surface of the laser radar, the water signal on the shell surface of the laser radar can be detected at least twice within a set total time period (i.e., water signals obtained by at least two laser radar detections of the shell surface are obtained); the current weather is determined based on the changes in the acquired water signals. The timing for determining the current weather can be after the current weather is determined based on a particular acquired water signal, or at the end of the total time period.

[0267] In the process of acquiring water signals obtained by detecting the shell surface using a laser radar at least twice within a set total time period, the time interval between two adjacent water signal acquisitions can be fixed (for example, acquiring a water signal every 5 seconds) or can be flexibly set based on the detected environmental parameters. The position of the lawn mower can be the same when acquiring water signals at different times, that is, the water signals obtained by acquiring the shell surface using a laser radar at least twice in a stationary state, or it can be different, for example, the position and / or posture of the lawn mower is adjusted each time a water signal is acquired.

[0268] Within a set total time period, water signals obtained by at least two laser radar detections of the shell surface can be obtained. The set total time period can be a time period of a specified duration set based on the first detection of the water signal, for example, a time period of 20 seconds starting from the moment the water signal was first detected. Based on each water signal obtained, the current weather can be determined according to different conditions until the determination condition is met or the total time period expires. Here, the determination condition can be a condition for determining whether the current weather is severe weather or a certain type of weather, or it can be other conditions that are pre-set or adjusted according to user needs.

[0269] The lawn mower can be controlled to perform corresponding actions based on the current weather. The actions corresponding to different weather conditions can be pre-set or adjusted according to user needs. The method of controlling the lawn mower to perform corresponding actions based on the current weather is similar to that in the previous embodiment and has been described, so it will not be repeated here.

[0270] Through the above steps, when there are water stains on the shell surface of the laser radar, water signals obtained by detecting the shell surface by the laser radar at least twice within the set total time period are obtained, and the current weather is determined based on the water signal obtained each time; the lawn mower is controlled to perform corresponding actions according to the current weather; including, when it is determined that the current weather is bad weather, shielding action is performed on at least part of the lawn mower, which can improve the accuracy of the current weather judgment, avoid weather damage to the lawn mower or affect the normal operation of the lawn mower, ensure the safety of the lawn mower, and increase the service life of the lawn mower.

[0271] On lawn mowers, using lidar for rain detection offers significant advantages over traditional rain sensors. Rain sensors detect the presence or flow of rain using changes in resistivity. When rain falls on the sensor surface, it changes its resistivity, generating an electrical signal. By detecting changes in this electrical signal, the presence of rain is detected. A drawback of rain sensors is that any water stain on the sensor's surface is interpreted as rain. They cannot distinguish between human spillage and accidental leaks, resulting in a false positive. Lawn mowers are not designed to operate in rainy conditions, causing them to stop mowing or return to the base station, reducing mowing efficiency. LiDAR addresses this limitation by determining whether the water signal on the surface is natural or artificial based on the water signal frame set and changes in the signal. This significantly improves detection accuracy and ensures efficient mowing. In addition, this embodiment obtains water signals obtained by detecting the shell surface by the laser radar at least twice within the set total time period to judge the current weather. Obtaining two water signals can compare and analyze the differences between the two water signals, thereby accurately distinguishing whether the water signal is caused by rain or human factors, reducing the probability of misjudgment.

[0272] In this embodiment, if the current weather is determined to be rainy, a shielding action is performed on at least a portion of the lawn mower. The shielding action is performed on at least a portion of the lawn mower to protect the laser radar or the lawn mower as a whole from the influence of the adverse external environment. Specifically, the action of avoiding adverse weather may include but is not limited to one of the following: controlling the lawn mower to return to a base station that matches the lawn mower, controlling the lawn mower to move to a designated location, and controlling a shielding member to shield at least a portion of the lawn mower (the laser radar, the body of the lawn mower, etc.) so that the lawn mower is at least partially shielded. The main working parts of the lawn mower include a cutter disc, a laser radar, and a drive wheel. Continuous operation in adverse weather conditions (such as rain) can cause the cutter disc to rust, the laser radar to become flooded, and the drive wheel to become stuck in mud, resulting in a shortened service life of the lawn mower.

[0273] When the main body of the laser radar is exposed to the external environment, it helps to detect weather conditions more accurately. However, when the main body of the laser radar is exposed to the external environment, its rainproof performance will be affected. The lawn mower just needs a non-rainy environment. Such conditions just meet the requirements for installing the laser radar on the lawn mower to detect bad weather.

[0274] In an exemplary embodiment, before obtaining the water signal obtained by detecting the shell surface by the laser radar at least twice within a set total time period, the above method also includes: setting the length of the total time period according to the temperature of the shell surface, wherein the length of the total time period is negatively correlated with the temperature of the shell surface.

[0275] Taking into account that the surface temperature of the lidar surface affects the evaporation rate of water (i.e., in a high temperature environment, the evaporation rate of water is accelerated; in a low temperature environment, the evaporation rate of water is slowed down), the length of the total time period can be set based on the temperature of the shell surface, where the length of the total time period is negatively correlated with the temperature of the shell surface.

[0276] Here, if the temperature of the shell surface is low and the water evaporates slowly, if the total time period is set to be short, for scenes without rain, the difference between the obtained water signals is small, and it is easy to be mistakenly judged as rainy weather; if the temperature of the shell surface is high and the water evaporates quickly, even if the total time period is set to be short, the difference between the obtained water signals can still accurately represent the current weather.

[0277] The correspondence between the shell surface temperature and the duration of the total time period can be preset and can be represented by a correspondence table, a correspondence curve, or other methods. Based on the correspondence between the shell surface temperature and the duration of the total time period, the duration of the total time period is set to the duration corresponding to the current shell surface temperature.

[0278] Through this embodiment, the duration of the total time period is set according to the temperature of the shell surface, which can improve the efficiency of the current weather determination while ensuring the accuracy of the current weather determination.

[0279] In an exemplary embodiment, the correspondence between the temperature of the shell surface and the duration of the set total time period can be preset, and the above correspondence can be predicted based on simulation data or actual experimental data.

[0280] In this embodiment, considering that the shell surface temperature is usually higher when operating outdoors, when the shell surface temperature is 35-60°C, in order to avoid the influence of high temperature on detection accuracy, the set total time can be 10-30S (seconds). For example, when the shell surface temperature is 35°C, the set total time can be 30S, and when the shell surface temperature is 60°C, the set total time can be 10S.

[0281] The detection time of water stains by the laser radar is negatively correlated with the surface temperature of the laser radar shell. Under the condition of the same detection accuracy, the higher the shell surface temperature, the shorter the detection time required, and the lower the shell surface temperature, the longer the detection time required. The shell surface temperature is positively correlated with the working time of the lawn mower. Generally speaking, after 10 minutes of operation, the shell surface temperature of the laser radar can reach 35°C in most cases (because the ambient temperature of the grass growing environment itself is not too low). After testing, when the shell surface temperature reaches 35°C and the detection time reaches 10S, the accuracy of detecting bad weather is greater than 86%. Moreover, the longer the laser radar works, the higher the shell surface temperature. When the working time reaches 30 minutes, the shell surface temperature of the laser radar can reach 40°C in most cases. At this time, when the detection time is set to 10S, the accuracy of detecting bad weather is greater than 93%. When the shell surface temperature of the laser radar reaches 60°C and the detection time is set to 10S, the accuracy of detecting bad weather is greater than 99%. Therefore, for users, under long-term usage conditions, when the detection time is set to 10 seconds, the overall probability of false positives in severe weather is less than 10%. Any false positives are usually misclassified as severe weather, which is not severe weather. This false positive does not affect the lifespan of the mower or the lidar. It only causes the mower to perform unnecessary weather avoidance maneuvers, affecting mowing efficiency. This is acceptable to users. If the detection time is less than 10 seconds, the false positive rate will increase sharply, significantly reducing the mower's efficiency and affecting the user experience. Testing has shown that when the housing surface temperature reaches 35°C in most cases and the detection time reaches 30 seconds, the accuracy rate for severe weather is greater than 96%. When the housing surface temperature reaches 40°C in most cases and the detection time is set to 30 seconds, the accuracy rate for severe weather detection is greater than 99%. Therefore, when the detection time reaches 30 seconds, the detection accuracy is sufficiently high and fully meets the inspection requirements. Increasing the detection time to greater than 30 seconds has a very small impact on detection accuracy, but it will increase the data processing load of the processing unit, shortening its service life.

[0282] Through this embodiment, when the temperature of the shell surface of the laser radar is 35-60°C, the duration of the total time period is set to 10-30S, which can improve the efficiency of the current weather judgment while ensuring the accuracy of the current weather judgment.

[0283] In an exemplary embodiment, the total time period is divided into multiple sub-time periods. The durations of different time periods within the multiple sub-time periods may be the same or different. The division criteria for the multiple sub-time periods may be pre-configured, for example, the total time period and the division criteria for the total duration may be configured to correspond to changes in the shell surface temperature. Alternatively, the division criteria may be directly set by the user on the user side, for example, a detection interval of 5 seconds. Other division criteria may also be used, and this is not limited in this embodiment.

[0284] Correspondingly, the water signal obtained by the laser radar detecting the shell surface at least twice within the set total time period is obtained, including: within the set total time period, the water signal obtained by the laser radar detecting the shell surface once at the end of each sub-time period in multiple sub-time periods.

[0285] The total time period can be divided into multiple sub-time periods. Correspondingly, the water signal obtained by the laser radar detecting the shell surface is continuously obtained within the set total time period, including: within the set total time period, the water signal obtained by the laser radar detecting the shell surface is obtained once at the end of each sub-time period in multiple sub-time periods.

[0286] In this embodiment, starting from the moment the water signal is first detected, a water signal is acquired once at a certain interval (which may be the end of a sub-time period of multiple sub-time periods). The total time period and multiple sub-time periods can be represented by the water signal being acquired once at certain intervals. For example, the total time period can correspond to the number of times the water signal is acquired, and the multiple sub-time periods can correspond to the time interval between two adjacent water signal acquisitions. The time interval between two adjacent water signal acquisitions can be the same or different.

[0287] Optionally, the end time of each sub-time period can be determined by setting a timer according to the duration of each sub-time period, and determining the end position of each sub-time period when the timer timing time is reached. Accordingly, starting from the moment when the water signal is first obtained, the timer timing time is set, and the timing time can be a specified fixed time or a time set based on the temperature of the shell surface; when the timer timing time is reached (that is, the timer times out), a water signal is obtained once and the current weather is determined. If the current weather cannot be determined, the timer timing time is reset; and so on, until the number of water signals obtained reaches the specified number.

[0288] Through this embodiment, within the set total time period, a water signal is acquired once every time interval (corresponding to a sub-time period), which can improve the efficiency and controllability of water signal acquisition.

[0289] In an exemplary embodiment, the durations of different time periods in the multiple sub-time periods may be the same or different. Considering the number of timers required and the complexity of the current weather determination, in this embodiment, the durations of the sub-time periods may be set to be equal, for example, each sub-time period may be set to be 5 seconds.

[0290] Through this embodiment, the duration of each sub-time end is set to be equal, which can reduce the number of timers that need to be set and reduce the complexity of current weather determination.

[0291] In an exemplary embodiment, to improve the timeliness and accuracy of current weather determination, the total time period should be neither too long nor too short, and the time periods should be appropriately divided. In this embodiment, when the total time period is 15 seconds, the total time period is divided into three sub-time periods, each of which is 5 seconds long. The total time period of 15 seconds can be set based on the temperature of the housing surface, a preset fixed value, or other methods.

[0292] It should be noted that the durations of different sub-time periods within multiple sub-time periods can be the same. The number of sub-time periods within a multiple sub-time period can be three, and the duration of a single sub-time period can be the duration of the total time period / 3. For a total time period of 15 seconds, each sub-time period is 5 seconds long. For other total time period lengths, the total time period can be divided into three sub-time periods using the same or similar division method.

[0293] Through this embodiment, when the total time period is 15 seconds, by dividing the duration of each sub-time period into 5 seconds, the efficiency and controllability of water signal acquisition can be improved, thereby improving the timeliness and accuracy of current weather judgment.

[0294] In an exemplary embodiment, water signals obtained by detecting the shell surface by the laser radar at least twice within a set total time period include: obtaining water signals obtained by detecting the shell surface by the laser radar at different postures within the set total time period.

[0295] Water stains on the lidar's housing can be caused by a variety of factors, including rain and continuous water spraying (for example, when watering a lawn). Therefore, in addition to rain, there are other situations in which water signals can be continuously detected on the lidar's housing. To ensure the accuracy of current weather determination, the current weather determination can be made by combining water signals detected by the lidar at different positions.

[0296] Correspondingly, within the set total time period, water signals obtained by the laser radar detecting the shell surface in different postures (positions and / or attitudes) can be obtained. After obtaining the water signal in a certain posture, if it is necessary to continue to obtain the water signal, the posture of the laser radar (at least one of the position and attitude) can be adjusted and the water signal can be obtained again in the new posture. Adjusting the posture of the laser radar can be achieved by adjusting the posture of the lawn mower, or by adjusting the posture of the laser radar.

[0297] Through this embodiment, the water signal obtained by the laser radar detecting the shell surface at different postures is obtained, which can improve the accuracy of the current weather judgment.

[0298] In an exemplary embodiment, obtaining a water signal obtained by a laser radar detecting a shell surface at different postures includes: obtaining a water signal obtained by a laser radar detecting a shell surface when a lawn mower moves to different positions, wherein the posture of the laser radar is different when the lawn mower moves to different positions.

[0299] As the mower continues to move, its position changes, and so does the LiDAR's posture. In this embodiment, water signals can be obtained from the LiDAR detecting the shell surface as the mower moves to different positions. The movement of the mower can be either the actual mowing operation or the control of the mower's movement to obtain corresponding water signals at different postures.

[0300] The timing for acquiring the water signal can be that the time interval between two adjacent water signal acquisitions is a specified time interval, or that the distance between the positions of the lawn mower when two adjacent water signals are acquired is a specified distance. It can also be other acquisition times, as long as it can be ensured that the acquired water signal is the water signal obtained by the laser radar detecting the shell surface when the lawn mower moves to different positions.

[0301] By obtaining the water signal obtained by the lidar detecting the shell surface at different postures within the set total time, some misjudgments can be eliminated, such as misjudging a non-raining situation as raining. The following scenarios will cause the above-mentioned misjudgments: the lawn mower moves under a high drain pipe, the lawn mower moves under a leaking water container, the lawn mower moves under a swing with an overturned beverage bottle placed on the swing. These situations will cause the lidar to continuously detect water signals on the shell surface. If the position is not moved, the lidar will misjudge this situation as rain, thereby controlling the lawn mower to perform unnecessary actions, such as returning to the base station, thereby reducing mowing efficiency.

[0302] Through this embodiment, the water signal obtained by the laser radar detecting the shell surface when the lawn mower moves to different positions is obtained, which can improve the convenience of current weather judgment while ensuring the working efficiency of the lawn mower.

[0303] In one exemplary embodiment, a signal detection condition may be set, i.e., a condition that the laser radar satisfies when detecting the shell surface. The signal detection condition may be a posture condition that may include at least one of the following: a different direction from the previous water signal acquisition; a different position from the previous water signal acquisition; or a specified distance from the previous water signal acquisition position.

[0304] Correspondingly, in this embodiment, the water signal obtained by the laser radar detecting the shell surface in different postures is obtained, including: when the lawn mower is in a working state, the water signal obtained by the laser radar detecting the shell surface for the first time; controlling the lawn mower to move or rotate to a detection posture that meets the signal detection conditions, and obtaining the water signal obtained by the laser radar detecting the shell surface when the lawn mower is in the detection posture that meets the signal detection conditions.

[0305] When the lawn mower is in operation, the water signal obtained by the laser radar detecting the shell surface is obtained for the first time. That is, the water signal obtained by the laser radar detecting the shell surface is obtained for the first time (the process of obtaining a water signal from nothing). At this time, the lawn mower can be controlled to move or rotate to a detection posture that meets the signal detection conditions. When the lawn mower moves or rotates to a detection posture that meets the signal detection conditions, the water signal obtained by the laser radar detecting the shell surface is obtained. After each water signal is obtained, the current weather can be determined. If it is necessary to obtain a water signal, the lawn mower's posture can be adjusted in the same or similar manner as described above.

[0306] Through this embodiment, the detection posture of the laser radar for detecting water signals is controlled by signal detection conditions, which can improve the convenience of controlling the lawn mower. At the same time, the accuracy of the current weather judgment can be improved by using the water signals detected under different detection postures to judge the current weather.

[0307] In one exemplary embodiment, a determination condition for determining whether to continue acquiring water signals may be set. For example, a first determination condition may be a condition for determining whether water stains on the lidar surface are not caused by inclement weather. Accordingly, determining the current weather based on each acquired water signal includes determining the current weather according to the first determination condition until the first determination condition is satisfied or the total time period expires.

[0308] When determining the current weather using the first determination condition, if the first determination condition is met, it can be determined that the current weather is not inclement weather. At this point, the current weather has been determined and no further determination is required. If the first determination condition is not met, it is impossible to determine whether the current weather is inclement weather. If the total time period has not expired, water signal acquisition can continue. Similar to the previous embodiment, the inclement weather to be determined may include, but is not limited to, at least one of the following: rain, hail, snow, and fog, which have already been explained and will not be repeated here.

[0309] Optionally, the first judgment condition can be a judgment condition set based on one or more specified parameters characterizing the water signal (for example, all or part of the shape of the water, the area covered by the water, and the position covered by the water). It can be a judgment condition related to the water signal acquired currently, or it can be a judgment condition related to the water signal acquired currently and the water signal acquired previously or the time before that (in this case, the first judgment condition can be a judgment condition related to the difference between water signals acquired at different times).

[0310] Optionally, after the first determination condition is met, the current weather can continue to be determined based on the acquired water signal, or the process of determining the current weather based on the acquired water signal can be ended, but the water signal on the shell surface of the lidar can still be detected through the lidar, and after obtaining the water signal, the total time period can be reset and the above-mentioned current weather determination steps can be executed.

[0311] Through this embodiment, by determining whether the water stains on the surface of the lidar are caused by bad weather based on the water signal obtained each time, and then determining the subsequent operations based on the determination result, the efficiency of current weather determination can be improved.

[0312] In an exemplary embodiment, the current weather is determined according to a first determination condition until the first determination condition is met or the total time period ends, including: when it is determined that the first determination condition is met based on the water signal obtained for the mth time, it is determined that the current weather is not bad weather; when none of the water signals obtained within the total time period meet the first determination condition, it is determined that the current weather is bad weather.

[0313] In this embodiment, the first determination condition can be one of the following: the water signal disappears; the water signal decreases to a specified value; the water signal decreases to a specified percentage. That is, if the water signal disappears, it can be determined that the current weather is not severe; if the water signal acquired after a period of time becomes significantly weaker, it can be determined that the current weather is not severe. Based on the above first determination condition, it can be determined that the water stain on the lidar surface is not caused by severe weather.

[0314] Correspondingly, determining the current weather according to the first determination condition may include: determining that the current weather is not inclement weather if the first determination condition is satisfied based on the water signal obtained for the mth time; and determining that the current weather is inclement weather if none of the water signals obtained within the total time period satisfy the first determination condition. Here, m is a positive integer greater than or equal to 2.

[0315] Optionally, when determining the current weather, a first threshold for obtaining water signals may be set. The set first threshold may be a positive integer greater than or equal to 2, and the first threshold corresponds to the total time period. Accordingly, water signals obtained by detecting the shell surface by a laser radar at least twice may be obtained until the first determination condition is satisfied based on a water signal obtained once, or the total time period ends (at which point the number of times the water signal is obtained reaches the first threshold).

[0316] For example, if the first threshold value is set to 3, the total time period can be understood as the time period from the time when the water signal is first obtained to the time when the water signal is third obtained (or a time after the time when the water signal is third obtained). In this case, if the number of water signals obtained reaches the first threshold value and none of the obtained water signals meet the first determination condition, it can be determined that the current weather is inclement weather.

[0317] Through this embodiment, it is determined that the current weather is not severe weather based on the disappearance of the water signal or the reduction of the water signal to a specified value, which can improve the accuracy and efficiency of weather determination.

[0318] In an exemplary embodiment, a determination condition can be set for determining whether to continue acquiring water signals, such as a second determination condition. This second determination condition can be a condition for determining whether the water stain on the lidar surface is not caused by inclement weather. The second determination condition is the same as or similar to the first determination condition in the aforementioned embodiment, or it can be a different determination condition. Correspondingly, based on each acquired water signal, the current weather is determined, including: determining the current weather according to the second determination condition until the second determination condition is satisfied or the number of water signal acquisitions reaches a set threshold number of times.

[0319] The second number threshold defines the maximum number of times a water signal is acquired. The second number threshold and the first number threshold may be the same or different, may be pre-set, or may be adjusted according to user needs. For example, the second number threshold may be 3 or other values. If, before the number of times a water signal is acquired reaches the set second number threshold, it is determined that the second judgment condition is met based on the change of a water signal acquired once, or two adjacent water signals acquired, then the current weather has been determined (i.e., it is not bad weather), and the above judgment process can be terminated; when the number of times a water signal is acquired reaches the set second number threshold, the water signal acquired once, or any two adjacent water signals acquired, do not meet the second judgment condition, then the current weather has been determined (i.e., it is bad weather).

[0320] Optionally, when the water signal is acquired twice adjacently, the position change of the laser radar may be the same or different. For example, when the water signal is acquired twice adjacently, the distance moved by the laser radar or the lawn mower is the same.

[0321] Through this embodiment, the current weather judgment is performed based on the condition that the water stains on the surface of the laser radar are not caused by bad weather and the set number threshold, which can improve the efficiency of the current weather judgment.

[0322] In an exemplary embodiment, the current weather is determined according to a second determination condition until the second determination condition is met or the number of times the water signal is acquired reaches a set threshold number, including: when it is determined based on the changes in the water signal acquired for the nth time and the water signal acquired for the n-1th time that the second determination condition is met, it is determined that the current weather is not bad weather; when the number of times the water signal is acquired reaches a set threshold number and the acquired water signals do not meet the second determination condition, it is determined that the current weather is bad weather.

[0323] In this embodiment, the second judgment condition may be: the coverage area of ​​the water signal decreases and / or the water signal coverage points do not increase, that is, it can be determined that the water stains on the shell surface have not increased through the fact that the coverage area of ​​the water signal obtained twice adjacently decreases and / or the water signal coverage points do not increase. It can be considered that the water stains on the shell surface have not increased due to rain, fog condensation and other phenomena caused by bad weather. It can be determined that the second judgment condition is not met, and it can be determined that the current weather is not bad weather.

[0324] Correspondingly, determining the current weather according to the second determination condition may include: determining that the current weather is not inclement weather if the second determination condition is satisfied based on the changes in the water signal obtained the nth time and the water signal obtained the n-1th time; and determining that the current weather is inclement weather if the number of water signal acquisitions reaches a set threshold and none of the acquired water signals meet the second determination condition. Here, n is a positive integer greater than or equal to 2. The second threshold is similar to the first threshold in the aforementioned embodiment and has been described, so it will not be repeated here.

[0325] Through this embodiment, the current weather is determined based on the changes in the water signals obtained twice adjacently, which can improve the efficiency and accuracy of the current weather determination.

[0326] In an exemplary embodiment, the method further includes: determining the coverage area and coverage position of the acquired water signal based on the points where the water signal is detected on the shell surface, wherein whether the water signal coverage point increases is determined based on the coverage position of the water signal.

[0327] In this embodiment, the coverage area and coverage points of the water signal can be determined by the points on the shell surface where the water signal is detected. A set of points can be configured for the shell surface of the laser radar (which can be pre-set or set after it is determined that the water signal needs to be acquired). When acquiring the water signal, it can be determined whether the water signal is detected at each configured point, and the points where the water signal is detected in the set of points can be obtained. The area covering the points on the shell surface where the water signal is detected can be used as the coverage area of ​​the water signal, thereby determining the coverage area and coverage position of the acquired water signal.

[0328] When determining whether the water signal coverage points have increased, the determination can be made directly based on the location and number of the points where the water signal was detected, or based on the coverage position of the water signal. In scenarios where the determination of whether the water signal coverage points have increased is made directly based on the points where the water signal was detected, if there is no other need to use the water signal coverage area and coverage position, the step of determining the acquired water signal coverage area and coverage position based on the points where the water signal was detected on the shell surface can be omitted.

[0329] Through this embodiment, the coverage area and coverage position of the acquired water signal are determined according to the point position where the water signal is detected on the shell surface, which can improve the convenience of determining the coverage area and coverage position of the water signal.

[0330] The following describes the lawn mower control method of this embodiment with reference to an optional example. This optional example provides a solution for determining the current weather by determining whether water stains are present at different locations. When a water signal is first detected, the location of water on the sensor surface is recorded, and an algorithm is used to calculate the water coverage area and corresponding location.

[0331] The lawn mower moves to the next position, records the points where water is detected on the sensor surface, and calculates the water coverage area and the corresponding coverage position through an algorithm. The water coverage changes between the two positions are compared. If the water coverage area decreases and no new water coverage points are added, it indicates that there are no new water stains. Otherwise, it enters the next position to continue detection and judgment, that is, continue to compare the water coverage changes between the two positions. If the water coverage area decreases and no new water coverage points are added, it indicates that there are no new water stains. Similarly, when entering the second-to-last position, detection and judgment continue, that is, continue to compare the water coverage changes between the two positions. If the water coverage area decreases and no new water coverage points are added, it indicates that there are no new water stains. Otherwise, it is determined that there are new water stains, and then the current weather is determined to be inclement weather, and the lawn mower is controlled to perform the corresponding operation.

[0332] It should be noted that each time the lawn mower enters the next position, the direction of the laser radar can be controlled to be different, or the distance between each two adjacent positions can be a specified distance. The lawn mower can also be restricted to the next position in other ways.

[0333] Through this optional example, the accuracy of weather determination can be improved by controlling the lawn mower to detect water signals at different positions and judging the current weather based on the changes in the water signals detected twice adjacently.

[0334] In an exemplary embodiment, when the current weather is judged to be severe weather, shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be severe weather, controlling the lawn mower to return to a base station matched with the lawn mower.

[0335] In this embodiment, if the current weather is determined to be inclement, the lawn mower can be controlled to return to the base station that matches the lawn mower to prevent the inclement weather from damaging the lawn mower. The location of the base station and the matching relationship between the base station and the lawn mower in this embodiment are similar to those in the previous embodiment and have been explained above and will not be repeated here.

[0336] Through this embodiment, when it is determined that the current weather is severe, the lawn mower is controlled to return to the base station that matches the lawn mower, thereby improving the safety of the lawn mower operation and the timeliness of the lawn mower control.

[0337] In one exemplary embodiment, when the current weather is determined to be inclement, shielding at least a portion of the lawn mower includes controlling the lawn mower to move to a designated location such that at least a portion of the lawn mower is shielded. The designated location in this embodiment can be under the eaves of a building, under an awning, or any other sheltered location. After the lawn mower reaches the designated location, it can continue mowing at the designated location or stop and park.

[0338] In this embodiment, if the current weather is judged to be bad weather, the lawn mower can be controlled to move to a designated location to prevent the bad weather from damaging the lawn mower. The designated location and the method for setting the designated location in this embodiment are similar to those in the previous embodiment and have been explained, so they will not be repeated here.

[0339] In an exemplary embodiment, when the current weather is judged to be inclement weather, a shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be inclement weather, controlling a shielding member to shield the laser radar, and the shielding member can be set on the lawn mower or outside the lawn mower. When the shielding member is set on the lawn mower, a control unit can be used to control the shielding member to shield the laser radar under inclement weather conditions, and retract under non-inclement weather conditions to expose the laser radar so that the lawn mower can operate normally; when the shielding member is set outside the lawn mower, a control unit can be used to control the shielding member to move to the position of the laser radar under inclement weather conditions to form a shield for the laser radar, and move away from the laser radar under non-inclement weather conditions to remove the shielding for the laser radar.

[0340] In an exemplary embodiment, when the current weather is judged to be inclement weather, a shielding action is performed on at least part of the lawn mower, including: when the current weather is judged to be inclement weather, controlling a shielding member to shield the body of the laser radar, the shielding member can be set on the lawn mower or can be set outside the lawn mower. When the shielding member is set on the lawn mower, a control unit can be used to deploy the shielding member to form a shield for the laser radar or retract the shielding member to remove the shielding for the laser radar; when the shielding member is set outside the lawn mower, the shielding member can be a movable canopy. When the current weather is judged to be inclement weather, the canopy can be moved to the outside of the lawn mower to form a shield for the lawn mower. When the current weather is judged to be not inclement weather, the canopy can be removed from the lawn mower, allowing the lawn mower to operate normally.

[0341] Through this embodiment, when it is determined that the current weather is bad weather, the lawn mower is controlled to move to a designated location, which can improve the safety of the lawn mower's operation and increase the service life of the lawn mower.

[0342] In an exemplary embodiment, the method further comprises: controlling the lawn mower to stop mowing when water stains are present on the surface of the housing, wherein the cutting assembly of the lawn mower is lifted after the mowing is stopped.

[0343] The lawn mower further comprises a cutting assembly for performing the mowing operation. The position, working mode, type, etc. of the cutting assembly are similar to those in the aforementioned embodiment and have been described, so they will not be described in detail here.

[0344] If there are water stains on the shell surface, considering that the water stains may be caused by bad weather, in order to ensure the safe operation of the cutting component, when there are water stains on the shell surface, the lawn mower is controlled to stop mowing. After the mowing work is stopped, the cutting component of the lawn mower is lifted up, so as to improve the convenience of moving the lawn mower while increasing the service life of the cutting component.

[0345] Through this embodiment, when there are water stains on the shell surface, the lawn mower can be controlled to stop mowing. After stopping mowing, the cutting component of the lawn mower is lifted up, which can reduce the risk of damage to the cutting component, improve the convenience of moving the lawn mower, and thus increase the service life of the cutting component.

[0346] In an exemplary embodiment, controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is determined that the current weather is not severe weather, controlling the lawn mower to continue mowing according to a preset cutting path and cutting mode.

[0347] In this embodiment, to ensure mowing efficiency, if the current weather is determined to be non-inclement, the lawn mower can be controlled to continue mowing, for example, according to a pre-set cutting path and cutting pattern. The method for controlling the lawn mower to continue mowing is similar to that in the previous embodiment and has been described, so it will not be repeated here.

[0348] Through this embodiment, when it is determined that the current weather is not severe weather, the lawn mower is controlled to continue mowing according to the pre-set cutting path and cutting mode, thereby ensuring the mowing efficiency of the lawn mower.

[0349] In an exemplary embodiment, the method further includes: when there is water stain on the surface of the housing, before determining the current weather, the lawn mower continues mowing according to a preset cutting path and cutting pattern.

[0350] In this embodiment, to ensure mowing efficiency, the lawn mower can be controlled to continue mowing before the current weather is determined, for example, by continuing to mow according to a pre-set cutting path and cutting pattern. The method for controlling the lawn mower to continue mowing is similar to that in the previous embodiment and has been described, so it will not be repeated here.

[0351] Through this embodiment, before the current weather is determined, the lawn mower is controlled to continue mowing according to the preset cutting path and cutting mode, thereby ensuring the mowing efficiency of the lawn mower.

[0352] According to another aspect of the embodiment of the present application, a lawn mower control method is also provided. The method embodiment provided in the embodiment of the present application can be executed in a lawn mower (as shown in Figure 1) or a similar processing device. It has been explained and will not be repeated here.

[0353] The lawn mower control method provided in this embodiment can be executed by the lawn mower alone, or by the user terminal or the base station and the lawn mower together. Taking the lawn mower as an example, as shown in FIG11 , the process of the lawn mower control method includes the following steps:

[0354] S1102, when there is water stain on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once;

[0355] S1104 : When the coverage value of the single water signal obtained on the shell surface that increases per unit time is greater than a preset value, the lawn mower is controlled to continue mowing according to a preset cutting path and cutting mode.

[0356] Similar to the aforementioned embodiment, the lawn mower control method in this embodiment can be applied to the scenario of target detection for a lawn mower or similar equipment. The lawn mower may include a laser radar, the number and setting position of the laser radar, the characterization parameters of the water signal, and the way in which the lawn mower obtains the water signal by detecting the shell surface by the laser radar are similar to those in the aforementioned embodiment and will not be described in detail here. During the operation of the lawn mower, the laser radar can detect the shell surface and obtain the laser radar data; by parsing the laser radar data, the water signal of the above-mentioned shell surface can be obtained. In the case where there is water stain on the shell surface of the laser radar, the water signal obtained by the laser radar detecting the shell surface once can be obtained.

[0357] Considering that water stains on the surface of a lawn mower are not necessarily caused by inclement weather (e.g., rain, condensation of fog, melting hail, etc.), other sources are also possible. For example, there is the possibility that water signals are detected on the surface of the lawn mower due to human splashing of water, or water spraying by other machines. For water stains caused by inclement weather, it takes a certain amount of time to cover the shell surface. However, water stains caused by reasons such as human splashing of water will quickly and extensively cover the shell surface. In addition, water stains caused by inclement weather cover the shell surface more evenly than water stains caused by other reasons. Water stains caused by other reasons usually cover local areas of the shell surface. Therefore, whether the generation of water signals is caused by inclement weather is determined by whether the coverage value of a single water signal added to the shell surface per unit time is greater than a preset value. If the coverage value of a single water signal added to the shell surface per unit time is greater than the preset value, it is determined that the source of the water signal may be other than inclement weather, and the current weather is not inclement weather. Exemplarily, inclement weather includes at least one of rain, hail, snow, and fog.

[0358] Here, the specific duration of the unit time and the preset value of the water signal can be pre-set and can be adjusted according to user needs. The value can be determined based on analysis of historical data (for example, based on experience value setting), or can be determined based on statistical experimental results. For example, the unit time can be 1s, 2s or other values, and the preset value can be a preset water signal coverage area, or other parameters, which are not limited in this embodiment.

[0359] Here, a single water signal can be used to represent a single, continuous, and enclosed water stain area. That is, whether the water signal represents a single, continuous, and enclosed water stain area can be determined based on one or more specified parameters characterized by the water signal (e.g., water coverage area, water coverage location, water shape, etc.). The judgment and analysis process for the water signal characterization parameters is similar to that in the aforementioned embodiment. The coverage value of a single water signal can be calculated based on one or more specified parameters characterized by the water signal, for example, based on the water signal area and water signal strength. The calculation process and used parameters can be pre-set or adjusted according to user needs.

[0360] According to the current weather, the lawn mower can be controlled to perform corresponding actions. For example, the lawn mower can be controlled to continue working or return to the corresponding base station according to whether the current weather is bad weather. The lawn mower can also be controlled to continue working or perform other preset actions according to the specific weather type of the current weather. In addition, the user can also control the lawn mower to perform the corresponding action selected by the user through the interactive interface or control terminal. When it is detected that the coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, it can be determined that the source of the water signal may be other reasons other than bad weather, that is, it can be determined that the current weather is not bad weather, and then the lawn mower can be controlled to perform corresponding actions, including: controlling the lawn mower to continue mowing according to the pre-set cutting path and cutting mode, thereby ensuring the working efficiency of the lawn mower.

[0361] Through the above steps, when there are water stains on the shell surface of the laser radar, a water signal obtained by the laser radar detecting the shell surface once is obtained; when the coverage value of a single water signal increased on the shell surface per unit time is greater than a preset value, it is determined that the current weather is not bad weather; the lawn mower is controlled to perform corresponding actions according to the current weather, which can eliminate the situation where water signals are detected on the shell surface due to reasons other than bad weather, thereby improving the accuracy of the current weather judgment.

[0362] In an exemplary embodiment, the coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, including: the coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to one third of the shell surface area.

[0363] Considering that water stains caused by severe weather usually cover the shell surface relatively slowly and evenly, and do not completely cover the shell surface in a short period of time, a threshold (an optional example of a preset value) for the coverage area of ​​a single water signal added per unit time can be set, for example, one-third or one-half of the shell surface area. If it is detected that the coverage area of ​​a single water signal added per unit time reaches the set coverage area threshold (for example, one-third or one-half of the shell surface area), it can be determined that the current weather is not severe weather.

[0364] Through this embodiment, by comparing the coverage area of ​​a single water signal added to the shell surface per unit time with the set coverage area threshold, it is determined whether the water stains on the shell surface are caused by bad weather, which can improve the accuracy of current weather judgment.

[0365] In an exemplary embodiment, the coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, including: the coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to 6 square centimeters.

[0366] In this embodiment, considering that the size differences of the laser radars on lawn mowers are usually not large, in order to improve the convenience of current weather determination, the above-mentioned coverage area threshold (specified value) can be a specified area threshold. Compared with the aforementioned coverage area threshold set according to a proportion (for example, one-third), it has a faster calculation speed because there is no need to know the area of ​​the shell surface and no need to calculate the proportion.

[0367] In this embodiment, the designated area threshold can be 6 square centimeters. When the coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to 6 square centimeters, it can be determined that the current weather is not severe. The designated area threshold can also be other values. Compared to other area thresholds, 6 square centimeters can be more suitable for actual scenarios and improve the accuracy of current weather determination.

[0368] Through this embodiment, when the coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to 6 square centimeters, it is determined that the current weather is not bad weather, which can improve the accuracy of the current weather determination.

[0369] In an exemplary embodiment, the coverage value of a single water signal added on the shell surface per unit time is greater than a preset value, including: a diameter of a single water signal added on the shell surface per unit time is greater than or equal to 2 centimeters.

[0370] Considering that water stains caused by severe weather are usually relatively slow and not very large, a threshold value (an optional example of a preset value) for the diameter of a single water signal that increases per unit time can be set, for example, 2 cm, 3 cm, 5 cm, etc. If the diameter of a single water signal that increases per unit time on the shell surface is greater than or equal to the set diameter threshold value (for example, 2 cm), it can be determined that the current weather is not severe weather.

[0371] Through this embodiment, by comparing the diameter of a single water signal increased on the shell surface per unit time with a set diameter threshold, it is determined whether the water stains on the shell surface are caused by bad weather, which can improve the accuracy of current weather judgment.

[0372] In an exemplary embodiment, the length of the unit time affects not only the timeliness of current weather determination but also the accuracy of detection. For example, if the unit time is too short, inclement weather may not be detected. If it is too long, inclement weather may not be detected in a timely manner, increasing the risk of damage to the lawn mower caused by inclement weather. It may also lead to inaccurate current weather determinations due to variations in the water signal that cannot accurately represent the current weather. To improve the timeliness and accuracy of current weather determinations, the unit time is less than or equal to 2 seconds.

[0373] According to this embodiment, by setting the length of the unit time to be less than or equal to 2 seconds, the timeliness and accuracy of the current weather determination can be improved.

[0374] Obviously, those skilled in the art should understand that the various modules or steps of the above-mentioned embodiments of the present application can be implemented using a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented using program codes executable by the computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be performed in a different order than herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0375] The above are only preferred embodiments of the present application and are not intended to limit the embodiments of the present application. For those skilled in the art, the embodiments of the present application may be modified and varied in various ways. Any modifications, equivalent replacements, improvements, etc. made within the principles of the embodiments of the present application shall be included in the scope of protection of the embodiments of the present application.

Claims

1. A target detection method for a lawn mower, comprising: Acquire a target frame set obtained by detecting a sensor shell surface of the target sensor through a target sensor, wherein each target frame in the target frame set is a single-frame point cloud obtained by one detection by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; Performing a projection operation on the target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; The target projection image is input into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model used to distinguish multiple preset categories, and the target classification result is used to indicate a preset category among the multiple preset categories that matches the target frame set.

2. The method according to claim 1, wherein: The acquiring of a target frame set obtained by detecting a sensor shell surface of the target sensor through the target sensor includes: Acquire multiple groups of echo signals obtained by transmitting detection signals multiple times by the target sensor to the surface of the sensor housing, wherein each group of echo signals in the multiple groups of echo signals includes two echo signals corresponding to a detection signal transmitted once; The two echo signals in each group of echo signals are fused into a corresponding single-frame point cloud to obtain the target frame set.

3. The method according to claim 2, wherein: One echo signal in each group of echo signals is an echo signal reflected by the surface of the sensor housing, and the other echo signal is an echo signal reflected by the detected target.

4. The method according to claim 2, wherein: The step of fusing two echo signals in each group of echo signals into a corresponding single-frame point cloud to obtain the target frame set includes: Based on the signal difference at the same position point of two echo signals in each group of echo signals, a single frame point cloud corresponding to each group of echo signals is determined to obtain the target frame set, wherein in the target frame set, the value of a position point corresponds to the signal difference between the two echo signal position points corresponding to the one position point.

5. The method according to claim 1, wherein: Each position point in each target frame is represented by a set of position parameters, and the value of each position point in each target frame is used to represent the degree of occlusion of the corresponding position point; Before performing the projection operation on the target frame set, the method further includes: A filtering operation is performed on the target frame set based on at least one position parameter to obtain the filtered target frame set, wherein the at least one position parameter belongs to the group of position parameters.

6. The method according to claim 5, wherein: The performing a filtering operation on the target frame set based on at least one position parameter to obtain the filtered target frame set includes at least one of the following: Filter out the position points in the target frame set whose corresponding modulus length is not a specified value, and obtain the target frame set after modulus length filtering; Position points in the target frame set whose corresponding polar angles are greater than or equal to a specified angle are filtered out to obtain the target frame set after polar angle filtering.

7. The method according to claim 5, wherein: The set of position parameters includes three axis coordinates in a rectangular coordinate system; the tilt angle of the target sensor includes a roll angle and a pitch angle; The performing a filtering operation on the target frame set based on at least one position parameter to obtain the filtered target frame set includes: Using a first rotation matrix and a second rotation matrix to transform the coordinate values ​​of the three axis coordinates of each position point in the target frame set, to obtain the target frame set after coordinate transformation, wherein the first rotation matrix is ​​a rotation matrix determined according to the roll angle, and the second rotation matrix is ​​a rotation matrix determined according to the pitch angle; The position points whose corresponding z-axis coordinates are less than a preset value in the target frame set after coordinate transformation are filtered out to obtain the target frame set after coordinate filtering.

8. The method according to claim 1, wherein: The performing a projection operation on the target frame set to obtain a target projection image includes: Projecting the target frame set into the specified plane to obtain target projection information corresponding to the target frame set, wherein the target projection information is used to represent the pixel position to which each position point in the target frame set is projected and the pixel value corresponding to each position point, and the pixel value corresponding to each position point is the pixel value of the pixel point projected into the specified plane by each position point; The target projection image is generated according to the pixel position to which each position point is projected and the pixel value corresponding to each position point.

9. The method according to claim 8, wherein: The step of generating the target projection image according to the pixel position to which each position point is projected comprises: In the case where there is a position point set projected to the same pixel position in the target frame set, an average value of pixel values ​​corresponding to the position points in the position point set is determined as the pixel value of the pixel position projected to the position point set in the target projection image; Determine the pixel values ​​corresponding to other position points in the target frame set except the position points in the position point set as the pixel values ​​of the pixel positions to which the other position points in the target projection image are projected; When there is a group of pixel positions whose pixel values ​​are not determined within the image area of ​​the target projection image, the designated pixel value is determined as the pixel value of the group of pixel positions in the target projection image.

10. The method according to claim 1, wherein: The target frame set is obtained by the target sensor detecting the surface of the sensor shell in one of a plurality of continuous time intervals; the classification result corresponding to each time interval in the plurality of continuous time intervals is the confidence level output by the target classification model and corresponding to each preset category in the plurality of preset categories; After inputting the target projection image into a trained target classification model to obtain a target classification result, the method further includes: Smoothing multiple confidences corresponding to the same preset category in the classification results corresponding to each time interval to obtain a smoothed confidence corresponding to each preset category; The preset category with the highest corresponding smoothing confidence among the multiple preset categories is determined as the target category corresponding to the multiple continuous time intervals.

11. The method according to claim 1, wherein: The method further comprises: Performing a training sample acquisition operation multiple times based on a reference sensor to obtain a training image sample set, wherein the reference sensor and the target sensor are sensors of the same model, and the labeling information of each training image sample in the training image sample set is used to indicate one of the multiple preset categories; Performing model training on the target classification model to be trained based on each training image sample and the annotation information of each training image sample to obtain the trained target classification model; The training sample collection operation includes: Acquire a reference frame set obtained by detecting the sensor housing surface of the reference sensor through the reference sensor, wherein each reference frame in the reference frame set is detected by the reference sensor. A single-frame point cloud obtained from one detection; A projection operation is performed on the reference frame set to obtain a training image sample.

12. The method according to any one of claims 1 to 11, wherein: The acquiring of a target frame set obtained by detecting a sensor shell surface of the target sensor through the target sensor includes: The target frame set obtained by detecting the laser radar shell surface of the multi-dimensional laser radar through the multi-dimensional laser radar is obtained, wherein the target sensor is the multi-dimensional laser radar.

13. The method according to claim 12, wherein: The multi-dimensional laser radar is a three-dimensional laser radar.

14. The method according to any one of claims 1 to 11, wherein: The target sensor is an integrated sensing device, and the target sensor is also used for at least one of the following: navigation, positioning, and obstacle avoidance.

15. The method according to any one of claims 1 to 11, wherein: The plurality of preset categories are used to represent at least one of the following targets: rain, hail, snow, sandstorm, and fog.

16. The method according to any one of claims 1 to 11, wherein: The surface of the sensor housing is a plane and / or a curved surface.

17. The method according to any one of claims 1 to 11, wherein: The target sensor is disposed at a front end region of the top of the lawn mower at an angle to the horizontal plane.

18. An object detection device for a lawn mower, comprising: an acquisition unit, configured to acquire a target frame set obtained by detecting a sensor shell surface of a target sensor through a target sensor, wherein each target frame in the target frame set is a single frame point cloud obtained by a detection performed by the target sensor, and the target sensor is a sensor configured on the lawn mower for generating a point cloud; A first execution unit is configured to perform a projection operation on a target frame set to obtain a target projection image, wherein the projection operation is an operation of projecting onto a specified plane; The input unit is configured to input the target projection image into a trained target classification model to obtain a target classification result, wherein the target classification model is a classification model used to distinguish multiple preset categories, and the target classification result is used to indicate a preset category among multiple preset categories that matches the target frame set.

19. A computer-readable storage medium, the computer-readable storage medium comprising a stored program, wherein: When the program is executed, the method according to any one of claims 1 to 17 is executed.

20. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 17 through the computer program.

21. A method for controlling a lawn mower, the lawn mower comprising a laser radar, the method comprising: In the case where there is water stain on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once, and judging the current weather based on the obtained water signal; Controlling the lawn mower to perform corresponding actions according to the current weather; The controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is determined that the current weather is bad weather, shielding at least part of the lawn mower.

22. The method according to claim 21, wherein: Before determining the current weather, the lawn mower continues mowing according to the preset cutting path and cutting mode.

23. The method according to claim 21, wherein: The shielding action performed on at least part of the lawn mower comprises: The lawn mower is controlled to return to a base station matched with the lawn mower, or the lawn mower is controlled to move to a designated position so that at least a part of the lawn mower is shielded.

24. The method according to claim 21, wherein: The shielding action performed on at least part of the lawn mower comprises: A shielding member is controlled to shield at least a portion of the lawn mower to isolate at least a portion of the lawn mower from external severe weather.

25. The method according to claim 21, wherein: The controlling the lawn mower to perform corresponding actions according to the current weather also includes: When it is determined that the current weather is bad weather, the lawn mower is controlled to stop mowing, wherein the cutting component of the lawn mower is lifted after the mowing is stopped.

26. The method of claim 21, wherein: The controlling the lawn mower to perform corresponding actions according to the current weather also includes: When it is determined that the current weather is not severe weather, the lawn mower is controlled to continue mowing according to a preset cutting path and cutting mode.

27. The method according to claim 26, wherein: In the case where there is water stain on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once, and judging the current weather based on the obtained water signal, including: Obtain a target frame set of water signals obtained by the laser radar detecting the shell surface at least once, compare the target frame set with a preset classification model after processing, and judge the target frame set according to the target classification result. Determine the current weather, wherein the preset classification model is classified according to different types of weather.

28. The method according to claim 27, wherein: The step of obtaining a target frame set of water signals obtained by the laser radar detecting the shell surface at least once, processing the target frame set and comparing it with a preset classification model, and determining the current weather according to the target classification result includes: The shell surface of the laser radar is detected J times within a detection cycle. If the judgment results of the first K detections in the J detections are all that the current weather is bad weather, then the final weather output is bad weather; if the judgment results of the first L detections in the J detections are all that the current weather is bad weather, and the judgment result of the L+1th detection is that the current weather is not bad weather, then enter the next detection cycle until the current weather is determined; if at least one detection result among the judgment results of the first L detections in the J detections is that the current weather is not bad weather, then the final output is that the current weather is not bad weather, where L<K≤J and J≥2.

29. The method according to claim 28, wherein: The J=3, the K=3, and the L=2.

30. The method of claim 28, wherein: The duration of the detection cycle is negatively correlated with the temperature of the shell surface.

31. The method according to claim 30, wherein: The duration of one detection cycle is 10-30S.

32. The method according to any one of claims 21 to 31, wherein: The severe weather includes at least one of rain, hail, snow and fog.

33. A method for controlling a lawn mower, the lawn mower comprising a laser radar, the method comprising: In the case where there is water stain on the shell surface of the laser radar, a water signal obtained by the laser radar detecting the shell surface at least twice within a set total time period, and the current weather is determined based on the obtained water signal; Controlling the lawn mower to perform corresponding actions according to the current weather; The controlling the lawn mower to perform corresponding actions according to the current weather includes: when it is determined that the current weather is bad weather, shielding at least part of the lawn mower.

34. The method of claim 33, wherein: The shielding action performed on at least part of the lawn mower comprises: The lawn mower is controlled to return to a base station matched with the lawn mower; or the lawn mower is controlled to move to a designated position so that at least a part of the lawn mower is shielded.

35. The method of claim 33, wherein: The shielding action performed on at least part of the lawn mower comprises: Control a shielding member to shield at least a portion of the lawn mower to block at least a portion of the lawn mower. Isolate from the bad weather outside.

36. The method of claim 33, wherein: The controlling the lawn mower to perform corresponding actions according to the current weather also includes: When it is determined that the current weather is bad weather, the lawn mower is controlled to stop mowing, wherein the cutting component of the lawn mower is lifted after the mowing is stopped.

37. The method of claim 33, wherein: The controlling the lawn mower to perform corresponding actions according to the current weather also includes: When it is determined that the current weather is not severe weather, the lawn mower is controlled to continue mowing according to a preset cutting path and cutting mode.

38. The method of claim 33, wherein: Before determining the current weather, the lawn mower continues mowing according to the preset cutting path and cutting mode.

39. The method of claim 33, wherein: Before acquiring at least twice the water signal obtained by the laser radar detecting the shell surface within the set total time period, the method further includes: The duration of the total time period is set according to the temperature of the shell surface, wherein the duration of the total time period is negatively correlated with the temperature of the shell surface.

40. The method of claim 39, wherein: When the temperature of the shell surface is 35-60° C., the total time period is 10-30 seconds.

41. The method of claim 33, wherein: The total time period is divided into a plurality of sub-time periods; The step of acquiring the water signal obtained by detecting the shell surface by the laser radar at least twice within the set total time period includes: Within the set total time period, a water signal obtained by the laser radar detecting the shell surface is acquired once at the end of each sub-time period in the multiple sub-time periods.

42. The method according to claim 41, wherein: The durations of the sub-time periods within the total time period are equal.

43. The method of claim 41, wherein: When the total time period is 15 seconds, the total time period is divided into three sub-time periods, and the length of each sub-time period is 5 seconds.

44. The method of claim 33, wherein: The step of acquiring the water signal obtained by detecting the shell surface by the laser radar at least twice within the set total time period includes: Within a set total time period, water signals obtained by the laser radar detecting the shell surface at different positions are obtained.

45. The method of claim 44, wherein: The step of obtaining a water signal obtained by detecting the shell surface by the laser radar at different positions includes: A water signal obtained by the laser radar detecting the shell surface when the lawn mower moves to different positions is obtained, wherein the posture of the laser radar is different when the lawn mower moves to different positions.

46. ​​The method of claim 44, wherein: The step of obtaining a water signal obtained by detecting the shell surface by the laser radar at different positions includes: When the lawn mower is in working state, obtaining a water signal obtained by the laser radar detecting the shell surface for the first time; Control the lawn mower to move or rotate to a detection posture that meets the signal detection conditions, and obtain a water signal obtained by the laser radar detecting the shell surface when the lawn mower is in the detection posture that meets the signal detection conditions, wherein the signal detection conditions include at least one of the following: a direction different from that when the water signal was obtained last time; a position different from that when the water signal was obtained last time; and a distance between the position and the position when the water signal was obtained last time is a specified distance.

47. The method of claim 33, wherein: The determining of the current weather based on the acquired water signal comprises: The current weather is determined according to a first determination condition until the first determination condition is satisfied or the total time period ends, wherein the first determination condition is a condition for determining that the water stains on the surface of the laser radar are not caused by bad weather.

48. The method of claim 47, wherein: The determining the current weather according to the first determination condition until the first determination condition is satisfied or the total time period ends includes: When it is determined that the first determination condition is satisfied based on the water signal obtained for the mth time, it is determined that the current weather is not bad weather, where m is a positive integer greater than or equal to 2; If the water signals acquired within the total time period do not satisfy the first determination condition, determining that the current weather is bad weather; The first determination condition is one of the following: the water signal disappears; the water signal decreases to a specified value relative to the first acquired water signal; the water signal decreases to a specified percentage compared to the first acquired water signal.

49. The method of claim 33, wherein: The determining of the current weather based on the acquired water signal comprises: The current weather is determined according to a second determination condition until the second determination condition is met or the number of acquisitions of the water signal reaches a set threshold number of times, wherein the second determination condition is a condition for determining that the water stains on the surface of the laser radar are not caused by bad weather.

50. The method of claim 49, wherein: The determining the current weather according to the second determination condition until the second determination condition is satisfied or the number of acquisitions of the water signal reaches a set number threshold includes: When it is determined that the second determination condition is satisfied based on the change of the water signal obtained for the nth time and the water signal obtained for the (n-1th time), it is determined that the current weather is not raining, where n is a positive integer greater than or equal to 2; When the number of acquisitions of the water signal reaches a set number threshold and the acquired water signals do not meet the second determination condition, determining that the current weather is bad weather; The second determination condition is that the coverage area of ​​the water signal decreases and / or the coverage points of the water signal do not increase.

51. The method of claim 50, wherein: The method further comprises: The coverage area and coverage position of the acquired water signal are determined according to the points where the water signal is detected on the shell surface, wherein whether the water signal coverage points are increased is determined based on the coverage position of the water signal.

52. A method according to any one of claims 33 to 51, wherein: The severe weather includes at least one of rain, hail, snow and fog.

53. A method for controlling a lawn mower, the lawn mower comprising a laser radar, the method comprising: In the case where there is water stain on the shell surface of the laser radar, obtaining a water signal obtained by the laser radar detecting the shell surface at least once; When the coverage value of the single water signal increased on the shell surface per unit time is greater than a preset value, the lawn mower is controlled to continue mowing according to a preset cutting path and cutting mode.

54. The method of claim 53, wherein: The coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, including: The coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to one third of the shell surface area.

55. The method of claim 53, wherein: The coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, including: The coverage area of ​​a single water signal added to the shell surface per unit time is greater than or equal to 6 square centimeters.

56. The method of claim 53, wherein: The coverage value of a single water signal added to the shell surface per unit time is greater than a preset value, including: The diameter of a single water signal added on the shell surface per unit time is greater than or equal to 2 centimeters.

57. The method of claim 53, wherein: The length of the unit time is less than or equal to 2 seconds.

Images