Self-moving mower and edge building method of self-moving mower

Abstract

The invention discloses a self-moving mower and an edge building method of the self-moving mower. The self-moving mower at least comprises a mower body; the walking wheel assembly is configured to support the machine body; the signal receiving unit is configured to receive a signal sent by first remote equipment so as to obtain external positioning data of the self-moving mower; the first sensor assembly is configured to detect environment information around the self-moving mower; the second sensor assembly is configured to detect the motion state of the self-moving mower; the fusion positioning unit is configured to position the self-moving mower according to the environment information and fuse external positioning data to generate a first positioning result; positioning the self-moving mower according to the motion state, and fusing external positioning data to generate a second positioning result; and fusing the first positioning result and the second positioning result to generate a final positioning result. According to the invention, data of a plurality of sensors are effectively fused, and the positioning accuracy of the self-moving mower is improved.

Description

Technical Field

[0001] The present application relates to a lawn mower, and more particularly to a self - moving lawn mower and a method for building the edge of a self - moving lawn mower. Background Art

[0002] When a lawn mower performs self - moving mowing, it is necessary to ensure the accuracy of the positioning result to guarantee the mowing efficiency. Therefore, it is difficult to ensure the accuracy of the positioning result by simply relying on a single sensor for positioning, and it is necessary to further improve the accuracy of the positioning result of the self - moving lawn mower.

[0003] Moreover, when a lawn mower performs self - moving mowing, it is necessary to construct a mowing map. In the prior art, the construction of the mowing map depends on manually controlling the lawn mower for construction, with low construction efficiency and difficult to ensure safety.

[0004] When a lawn mower performs mowing, the presence of environmental obstacles will have a certain impact on the mowing task of the lawn mower, and the power supply of multiple sensors on the lawn mower will have a certain impact on the battery life of the lawn mower.

[0005] This part provides background information related to the present application, and these background information are not necessarily prior art. Summary of the Invention

[0006] An object of the present application is to solve or at least alleviate some or all of the above problems. To this end, an object of the present application is to provide a self - moving lawn mower and a method for building the edge of a self - moving lawn mower.

[0007] To achieve the above object, the present application adopts the following technical solutions: A self - moving lawn mower, comprising: a body; a walking wheel assembly configured to support the body; a signal receiving unit configured to receive a signal sent by a first remote device to obtain external positioning data of the self - moving lawn mower; a first sensor assembly configured to detect environmental information around the self - moving lawn mower; a second sensor assembly configured to detect the motion state of the self - moving lawn mower itself; a fusion positioning unit disposed on the body and electrically connected to the signal receiving unit, the first sensor assembly and the second sensor assembly, the fusion positioning unit being configured to: position the self - moving lawn mower according to the environmental information and generate a first positioning result by fusing the external positioning data; position the self - moving lawn mower according to the motion state and generate a second positioning result by fusing the external positioning data; fuse the first positioning result and the second positioning result to generate a final positioning result.

[0008] A self - propelled lawn mower, comprising: a body; a traveling wheel assembly configured to support the body; a wireless communication module configured to communicate with a second remote device, including receiving a control signal sent by the second remote device; a vision sensor for acquiring image data around the self - propelled lawn mower; a controller electrically connected to the wireless communication module and the vision sensor respectively, acquiring the control signal and the image data; characterized in that the controller is configured to: calculate a moving route indicated by the control signal, control the traveling wheel assembly to make the self - propelled lawn mower travel along the moving route, and store coordinate information of the moving route; based on deep learning, identify the boundary between grass and non - grass in the image data, control the traveling wheel assembly to make the self - propelled lawn mower travel along the boundary, and store coordinate information of the boundary; integrate the coordinate information of the moving route and the coordinate information of the boundary to generate a working area boundary of the self - propelled lawn mower.

[0009] A method for establishing a boundary of a self - propelled lawn mower, the self - propelled lawn mower including a wireless communication module and a vision sensor, the method for establishing a boundary including: receiving, by the wireless communication module, a control signal sent by a second remote device; acquiring, by the vision sensor, image data around the self - propelled lawn mower; calculating a moving route indicated by the control signal, controlling the self - propelled lawn mower to travel along the moving route, and storing coordinate information of the moving route; when the control signal is missing, identifying the boundary between grass and non - grass in the image data, controlling the self - propelled lawn mower to travel along the boundary, and storing coordinate information of the boundary; integrating the coordinate information of the moving route and the coordinate information of the boundary to generate a working area boundary of the self - propelled lawn mower.

[0010] A self - propelled lawn mower, comprising: a body; a traveling wheel assembly configured to support the body; a signal receiving unit configured to receive a signal sent by a first remote device, the signal being used to determine the position of the self - propelled lawn mower; a vision sensor for acquiring image data around the self - propelled lawn mower; a controller electrically connected to the signal receiving unit and the vision sensor respectively; characterized in that the controller is configured to: receive the image data from the vision sensor; judge the signal quality of each area in the image data through a target detection algorithm; adjust the positioning fusion algorithm or perform path planning according to the signal quality of each area.

[0011] A self - propelled lawn mower, comprising: a body; a traveling wheel assembly configured to support the body; a plurality of sensor components disposed on the body; a controller electrically connected to the plurality of sensor components respectively; a power supply device disposed on the body, configured to supply power to the controller and the plurality of sensor components; characterized in that the controller is configured to: selectively cut off the power supply of the power supply device to at least one of the plurality of sensor components.

[0012] The advantages of the present application are as follows: 1) By fusing the external positioning data with the environmental information and the positioning of the motion state respectively, and then further fusing the fusion results for the final positioning, it avoids the positioning error caused by the single and irregular accumulation of visual features in the environment, and also avoids the positioning error caused by the single inaccuracy of the ground state on the motion state. It effectively fuses the data of multiple sensors and improves the positioning accuracy of the self-propelled lawn mower. 2) By visually identifying the boundary between grass and non-grass and combining the control signal of the second remote device, the lawn mowing map of the self-propelled lawn mower is constructed, which improves the construction efficiency of the lawn mowing map and the safety of map construction. 3) Based on the dual judgment of visual recognition and signal quality, the positioning fusion algorithm of the self-propelled lawn mower is adjusted or the path planning is carried out to guide the self-propelled lawn mower to perform the lawn mowing task safely and efficiently. According to the RTK working condition map, the positioning fusion algorithm is adjusted more robustly, and the path of the self-propelled lawn mower is adjusted, which improves the lawn mowing efficiency and safety of the self-propelled lawn mower. 4) By monitoring the different working condition tasks of the self-propelled lawn mower and selecting different sensor components for power supply according to the different working conditions determined by the monitoring, the self-propelled lawn mower can complete the lawn mowing task more efficiently and for a longer time, thus achieving the power saving and battery life function of the self-propelled lawn mower. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a schematic diagram of a self-propelled lawn mower according to an embodiment of the present application; Figure 2 is a schematic flow chart of a fusion positioning process of a fusion positioning unit configuration according to an embodiment of the present application; Figure 3 is a schematic architecture diagram of a method for configuring a fusion positioning unit according to an embodiment of the present application; Figure 4 is a schematic flow chart of a process for generating a working area boundary of a controller configuration according to an embodiment of the present application; Figure 5 is a schematic diagram of a moving scene when a self-propelled lawn mower constructs a working area map according to an embodiment of the present application; Figure 6 is a schematic diagram of a method for building an edge of a self-propelled lawn mower according to an embodiment of the present application; Figure 7 is a signal quality adjustment method of a controller configuration according to an embodiment of the present application; Figure 8 is a schematic diagram of a method for determining signal quality of a controller configuration on a self-propelled lawn mower according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] Before explaining any embodiments of the present application in detail, it should be understood that the present application is not limited to the structural details and component arrangements set forth in the following description or shown in the above drawings.

[0015] In the present application, the terms "comprise", "include", "have" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, article or device comprising that element.

[0016] In the present application, the term "and / or" describes the relationship between associated objects and represents three possible relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Additionally, in the present application, the character " / " generally indicates that the associated objects before and after are in an "and / or" relationship.

[0017] In the present application, the terms "connect", "combine", "couple", "mount" can be direct connections, combinations, couplings or mounts, or indirect connections, combinations, couplings or mounts. By way of example, a direct connection means that two parts or components are connected together without an intermediate member, and an indirect connection means that two parts or components are each connected to at least one intermediate member, and these two parts or components are connected through the intermediate member. In addition, "connect" and "couple" are not limited to physical or mechanical connections or couplings and can include electrical connections or couplings.

[0018] In the present application, those of ordinary skill in the art will understand that relative terms used in connection with a quantity or condition (such as "about", "approximately", "substantially", etc.) are intended to include the stated value and have the meaning indicated by the context. For example, such relative terms include at least the degree of error associated with the measurement of a particular value, tolerances resulting from manufacturing, assembly, use, etc. associated with a particular value. Such terms should also be considered to disclose a range defined by the absolute values of two endpoints. Relative terms may refer to a plus or minus a certain percentage (such as 1%, 5%, 10% or more) of the indicated value. Numerical values without the use of relative terms should also be disclosed as specific values with tolerances. In addition, when expressing a relative angular position relationship (such as substantially parallel, substantially perpendicular), "substantially" may refer to a plus or minus a certain number of degrees (such as 1 degree, 5 degrees, 10 degrees or more) based on the indicated angle.

[0019] In this application, those of ordinary skill in the art will understand that the functions performed by components can be performed by one component, multiple components, one part, or multiple parts. Similarly, the functions performed by parts can also be performed by one part, one component, or a combination of multiple parts.

[0020] In this application, the orientation terms such as "upper", "lower", "left", "right", "front", "rear", etc. are described based on the orientation and positional relationship shown in the drawings, and should not be construed as limiting the embodiments of this application. In addition, in the context, it should also be understood that when it is mentioned that one element is connected "above" or "below" another element, it can not only be directly connected "above" or "below" another element, but also be indirectly connected "above" or "below" another element through an intermediate element. It should also be understood that the orientation terms such as the upper side, the lower side, the left side, the right side, the front side, and the rear side not only represent the positive orientation, but can also be understood as the side orientation. For example, the lower side can include directly below, lower left, lower right, lower front, and lower rear, etc.

[0021] In this application, the terms "controller", "processor", "central processor", "CPU", "MCU" can be interchanged. When using the units "controller", "processor", "central processor", "CPU", or "MCU" to perform specific functions, unless otherwise specified, these functions can be performed by a single one of the above units or multiple ones of the above units.

[0022] In this application, the terms "device", "module", or "unit" can be implemented in the form of hardware or software in order to achieve specific functions.

[0023] In this application, the terms "calculate", "judge", "control", "determine", "identify", etc. refer to the operations and processes of a computer system or a similar electronic computing device (such as a controller, a processor, etc.).

[0024] Figure 1It is a schematic diagram of a self - propelled lawn mower according to an embodiment of the present application, including a lidar 1, a first sensor assembly 2, a wireless communication module 3, a signal receiving unit 4, a walking wheel assembly 5, and a working assembly 6. Among them, the first sensor assembly 2 is used to detect the environmental information around the self - propelled lawn mower. In one embodiment, the first sensor assembly 2 includes a vision sensor, such as a camera assembly. The wireless communication module 3, such as a Bluetooth module, a cellular network, a WiFi module, etc., enables the lawn mower to communicate with other remote devices through the wireless communication module 3. The signal receiving unit 4 is used to receive positioning signals, such as a GNSS receiver, a differential positioning unit. The walking wheel assembly 5 drives the self - propelled lawn mower to move. The working assembly 6 is used to support the main working functions of the self - propelled lawn mower. For example, it is a cutter head for mowing grass. This embodiment is applicable to the situation of optimizing the positioning accuracy of the self - propelled lawn mower. The optimization of the positioning accuracy is executed by a fusion positioning unit 7 in the self - propelled lawn mower, and this unit can be implemented in the form of a controller.

[0025] The self - propelled lawn mower includes a body, and the walking wheel assembly 5 is configured to support the body. Among them, the body of the self - propelled lawn mower refers to the hardware part for realizing the mowing function, and the walking wheel assembly refers to the component for supporting the automatic walking of the self - propelled lawn mower.

[0026] The self - propelled lawn mower further includes a signal receiving unit 4, configured to receive signals sent by a first remote device to obtain the external positioning data of the self - propelled lawn mower. Specifically, after receiving the signals sent by the first remote device, the signal receiving unit 4 processes the signals to obtain the external positioning data. The external positioning data is the position information obtained by the self - propelled lawn mower relying on the first remote device outside the lawn mower, such as GPS positioning data, etc. Exemplarily, the first remote device is a satellite. After the signal receiving unit receives the signal emitted by the satellite, it calculates the signal transmission time according to the emission time of the signal and the local time, then combines the speed of light to obtain the satellite - device distance, and further determines the position information according to the satellite - device distance.

[0027] In some embodiments, the signal receiving unit 4 is a Global Navigation Satellite System (GNSS) receiver. GNSS (Global Navigation Satellite System) is a navigation system that operates jointly using multiple satellites, ground receivers, and related devices. It can determine geographical locations, speeds, and times, etc. by receiving signals from satellites. GNSS mainly consists of several major systems such as the Global Positioning System (GPS), Galileo, GLONASS, and the BeiDou Navigation System. The goal of these systems is to provide high - precision navigation positioning and assisted navigation services globally.

[0028] Specifically, in the self - propelled lawn mower, a Global Navigation Satellite System (GNSS) receiver is configured to receive satellite signals and determine the external positioning data of the self - propelled lawn mower based on the satellite signals.

[0029] In some embodiments, the signal receiving unit 4 is a differential positioning unit, and the external positioning data is the differential positioning result of the self - propelled lawn mower.

[0030] The differential positioning unit refers to an internal device of the self - propelled lawn mower that determines external positioning data through a differential positioning method. Then, the external positioning data obtained by performing the differential positioning method on the signal through the differential positioning unit is the differential positioning result. Specifically, the signal receiving unit obtains RTK (Real - time kinematic) positioning data as the external positioning data through the RTK method. RTK is a measurement method that can obtain centimeter - level positioning accuracy in the field in real time.

[0031] The self - propelled lawn mower further includes a first sensor assembly 2 configured to detect the environmental information around the self - propelled lawn mower. In some embodiments, the first sensor assembly 2 includes a camera assembly.

[0032] The first sensor assembly 2 is configured with a camera assembly to detect the environmental information around the self - propelled lawn mower. That is, the first sensor assembly 2 is used to obtain information in the visual dimension, detect the environmental information around the self - propelled lawn mower through the information in the visual dimension, and can determine the visual positioning data in the visual dimension through the information in the visual dimension. Specifically, the camera assembly includes a binocular camera, etc.

[0033] The self - propelled lawn mower further includes a second sensor assembly 8 configured to detect the motion state of the self - propelled lawn mower itself. In some embodiments, the second sensor assembly 8 at least includes a wheel speed meter.

[0034] The second sensor assembly 8 is configured with a wheel speed meter to detect the motion state of the self - propelled lawn mower itself. The wheel speed meter is used to obtain the speed information of the wheels in the walking wheel assembly of the self - propelled lawn mower, and determine the motion positioning data through the speed information of the wheels.

[0035] In some embodiments, the second sensor assembly 8 further includes an IMU.

[0036] Specifically, the motion information can be obtained through the wheel speed meter in the second sensor assembly 8, and the motion positioning data can be obtained based on the motion information. In addition, in order to improve the accuracy of the motion positioning data, an IMU can also be set in the second sensor assembly 8, that is, the motion positioning data is determined by combining the data obtained from the wheel speed meter and the IMU.

[0037] The self - propelled mower further includes a fusion positioning unit 7, which is disposed on the body and electrically connected to the signal receiving unit 4, the first sensor assembly 2, and the second sensor assembly 8. The flow diagram of the fusion positioning process configured by the fusion positioning unit 7 is as shown in Figure 2 shown, and the specific process includes: S11. Locate the self - propelled mower according to the environmental information, and fuse the external positioning data to generate a first positioning result.

[0038] S12. Locate the self - propelled mower according to the motion state, and fuse the external positioning data to generate a second positioning result.

[0039] S13. Fuse the first positioning result and the second positioning result to generate a final positioning result.

[0040] The fusion positioning unit is electrically connected to the signal receiving unit, the first sensor assembly, and the second sensor assembly to obtain external positioning data, environmental information, and motion state, and fuse them to determine the final positioning result of the self - propelled mower. The architecture diagram of the fusion positioning unit configuration method is as shown in Figure 3 shown.

[0041] In some embodiments, S11 locates the self - propelled mower according to the environmental information and fuses the external positioning data to generate a first positioning result, including: Locate the self - propelled mower according to the environmental information, and fuse the external positioning data through Kalman filtering to generate a first positioning result.

[0042] Specifically, the environmental information includes the image information obtained by the camera assembly. Determine the visual positioning data of the self - propelled mower according to the image information, and fuse the visual positioning data and the external positioning data through Kalman filtering to generate a first positioning result.

[0043] Exemplarily, obtain environmental information through the camera assembly for VSLAM positioning to obtain visual positioning data, and then determine the first positioning result based on vision by fusing the VSLAM positioning data and the RTK external positioning data.

[0044] In some other feasible embodiments, image information can be obtained through the camera component in the first sensor component, and visual positioning data can be obtained based on the image information. In addition, in order to improve the accuracy of the visual positioning data, an IMU (Inertial Measurement Unit) can also be set in the first sensor component. An inertial measurement unit is a device that measures the three-axis attitude angle (or angular rate) and acceleration of an object. Generally, an IMU includes three single-axis accelerometers and three single-axis gyroscopes. The accelerometers detect the acceleration signals of the object on the independent three axes of the carrier coordinate system, while the gyroscopes detect the angular velocity signals of the carrier relative to the navigation coordinate system, measure the angular velocity and acceleration of the object in three-dimensional space, and calculate the attitude of the object based on this.

[0045] The first sensor component includes a camera component and an IMU. Environmental information is obtained through the visual sensor and combined with the IMU to obtain the visual inertial odometer VIO of the self-propelled lawn mower as the visual positioning data. VIO uses Visual Odometry to estimate the attitude of the lawn mower from the camera images and combines the inertial measurements of the IMU on the fuselage to correct the errors caused by the rapid movement of the fuselage due to poor image capture, and obtains the visual positioning data.

[0046] Exemplarily, environmental information is obtained through the camera component and combined with the IMU to obtain the visual inertial odometer VIO of the self-propelled lawn mower, and then the visual inertial odometer VIO and the RTK external positioning data are combined to determine the first positioning result based on vision.

[0047] In some embodiments, S12 locates the self-propelled lawn mower according to the motion state and combines the external positioning data to generate a second positioning result, including: Locating the self-propelled lawn mower according to the motion state and combining the external positioning data through Kalman filtering to generate a second positioning result.

[0048] Specifically, the motion state includes the speed information obtained by the wheel speedometer. The motion positioning data of the self-propelled lawn mower is determined based on the speed information, and the motion positioning data and the external positioning data are combined through Kalman filtering to generate a second positioning result. The motion state includes the speed information obtained by the wheel speedometer and the inertial data obtained by the IMU. The motion positioning data is determined based on the speed information and the inertial data, and then the motion positioning data and the external positioning data are combined through Kalman filtering to generate a second positioning result.

[0049] In some embodiments, S13 combines the first positioning result and the second positioning result to generate a final positioning result, including: Adjust the fusion weights of the first positioning result and the second positioning result according to the visual positioning quality and / or the quality of the signal; Fuse the first positioning result and the second positioning result according to the fusion weights to generate a final positioning result.

[0050] The first positioning result is visual positioning data, and its accuracy depends on the visual positioning quality; the second positioning result is motion positioning data, and the motion state and external positioning data are fused in the second positioning data. Due to the relative accuracy of the motion state acquisition, the accuracy of the second positioning data mainly depends on the accuracy of the external positioning data, that is, depends on the quality of the signal; therefore, the fusion weights of the first positioning result and the second positioning result are adjusted according to the visual positioning quality and / or the quality of the signal. The first positioning result and the second positioning result are fused through Kalman filtering according to the fusion weights to obtain the final positioning result.

[0051] Exemplarily, if the visual positioning quality is greater than the first preset quality threshold, it is determined that the fusion weight of the first positioning result is greater than the fusion weight of the second positioning result; if the quality of the signal is less than the preset signal threshold, it is determined that the fusion weight of the first positioning result is greater than the fusion weight of the second positioning result; or if the visual positioning quality is less than the second preset quality threshold, it is determined that the fusion weight of the first positioning result is less than the fusion weight of the second positioning result, and the first preset quality threshold is greater than the second preset quality threshold. And the specific ratio of the fusion weights can be dynamically adjusted according to the specific conditions of the RTK signal quality and the visual positioning quality in the actual scenario, which is not limited here.

[0052] The beneficial effects of this embodiment: Through the positioning fusion of the external positioning data with the environmental information and the motion state respectively, and then further fusing the fusion results for final positioning, it avoids the positioning error caused by the accumulation of single irregular environments through visual features, and avoids the positioning error caused by the single inaccuracy of the ground state to the motion state, effectively fuses the data of multiple sensors, and improves the positioning accuracy of the self-propelled lawn mower.

[0053] This embodiment of the application is another self-propelled lawn mower, which can be combined with the self-propelled lawn mower in the above embodiment. The schematic diagram of the self-propelled lawn mower is as Figure 1 shown. This embodiment is applicable to the situation of optimizing the determination of the mowing working area of the self-propelled lawn mower. The optimization of the determination of the mowing working area is executed by the controller in the self-propelled lawn mower, and this device can be implemented in a software and / or hardware manner.

[0054] The self - propelled lawn mower includes a body and a walking wheel assembly. The walking wheel assembly is configured to support the body. Here, the body of the self - propelled lawn mower refers to the hardware part for realizing the lawn mowing function, and the walking wheel assembly refers to the component for supporting the automatic walking of the self - propelled lawn mower.

[0055] The self - propelled lawn mower further includes a wireless communication module configured to communicate with a second remote device, including receiving a control signal sent by the second remote device. The second remote device is used to control the self - propelled lawn mower to move by sending a control signal to the wireless communication module of the self - propelled lawn mower. The second remote device can be a remote control device, etc. In some embodiments, the second remote device is a mobile terminal. The user can send a control signal to the self - propelled lawn mower in the mobile terminal to remotely control the self - propelled lawn mower to move.

[0056] The wireless communication module is located in the self - propelled lawn mower and is used to receive the control signal sent by the second remote device, so that the self - propelled lawn mower can move according to the control signal. In some embodiments, the wireless communication module includes at least one of the following: Bluetooth, WiFi, and cellular signal. Exemplarily, the user sends a control signal to the wireless communication module through a mobile device. After the wireless communication module receives the control signal through at least one of the ways: Bluetooth, WiFi, and cellular signal, it controls the self - propelled lawn mower to move according to the control signal.

[0057] The self - propelled lawn mower further includes a vision sensor for acquiring image data around the self - propelled lawn mower. A vision sensor is deployed on the self - propelled lawn mower to be able to acquire the image data around the self - propelled lawn mower in real time when the self - propelled lawn mower is moving. In some embodiments, the vision sensor includes a binocular camera. The self - propelled lawn mower acquires the surrounding image data through the binocular camera to improve the coverage of the image data.

[0058] The self - propelled lawn mower further includes a controller electrically connected to the wireless communication module and the vision sensor respectively, and acquires the control signal and the image data. The flow chart of the process of generating the working area boundary configured by the controller is as Figure 4 shown, and the specific process includes: S21. Calculate the moving route indicated by the control signal, control the walking wheel assembly to make the self - propelled lawn mower travel along the moving route, and store the coordinate information of the moving route; S22. Based on deep learning, identify the boundary between grass and non - grass in the image data, control the walking wheel assembly to make the self - propelled lawn mower travel along the boundary, and store the coordinate information of the boundary; S23. Integrate the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self - propelled lawn mower.

[0059] The controller on the self - propelled lawn mower is used to obtain the control signal received by the wireless communication module and the image data obtained by the vision sensor, so as to control the movement of the self - propelled lawn mower according to the control signal and the image data.

[0060] Specifically, when receiving the control signal, calculate the movement route indicated by the control signal, control the self - propelled lawn mower to travel along the movement route, and store the coordinate information of the movement route; when the control signal is missing, identify the boundary between grass and non - grass in the image data, control the self - propelled lawn mower to travel along the boundary, and store the coordinate information of the boundary; integrate the coordinate information of the movement route and the coordinate information of the boundary to generate the working area boundary of the self - propelled lawn mower.

[0061] In the current prior art, most of the self - propelled lawn mowers construct the mowing map by manually controlling the mower to construct the mowing area map. This method is both time - consuming and cannot accurately represent the map. Therefore, this embodiment proposes a semi - automatic map construction method for visually identifying grass and non - grass. By identifying the grass and non - grass areas, the map boundary is determined, and then an effective mowing area is formed by connecting. Exemplarily, based on deep learning to identify the grass and non - grass areas, and the grass area is the area that the self - propelled lawn mower needs to cut. Therefore, dividing the grass area can form the mowing map. However, for non - connected areas, it is necessary to manually send a control signal through the second remote device to remotely control and go to the next grass area, or for a complex environment, manual control composition can also be selected. This embodiment not only ensures the safety of the mowing map construction but also improves the construction efficiency of the mowing map.

[0062] Exemplarily, when the self - propelled lawn mower constructs the working area map, it uses a vision sensor to capture images of the lawn and uses deep learning technology to identify the grass and non - grass areas in the images. Deep learning is a machine learning technology that can train neural networks to identify patterns and features in images. By training a deep learning model to identify the grass and non - grass areas in the lawn images and determine the boundary between the grass and non - grass areas. The deep learning model can be a convolutional neural network (CNN) that extracts features from the lawn images and outputs classification results, where each pixel is classified as grass or non - grass, and the boundary is determined by determining the boundary between grass and non - grass pixels.

[0063] After the boundary line in the image data acquired by the current vision sensor is determined, control the self-propelled lawn mower to travel along the boundary line. Specifically, by controlling the movement of the self-propelled lawn mower, move forward along the boundary line, and record the path information of the self-propelled lawn mower during the travel. The path information may include the starting point, the ending point, and the coordinates of each point on the path of the self-propelled lawn mower. The coordinate information can be determined using the built-in sensors of the self-propelled lawn mower or obtained through an external positioning system. For example, the coordinate information is obtained using the fusion positioning method in the above embodiment. In some embodiments, the self-propelled lawn mower further includes a differential positioning unit for obtaining the coordinate information. In some embodiments, the self-propelled lawn mower further includes a sensor assembly for obtaining the coordinate information. Specifically, referring to the above embodiment, it will not be elaborated here.

[0064] When the self-propelled lawn mower travels according to the boundary line acquired during the movement, if the boundary line is closed, a virtual channel is constructed through a control signal to control the self-propelled lawn mower to go to the next lawn. The self-propelled lawn mower can again autonomously identify the boundary line between the grass and the non-grass through the image data and continue to construct the map. Specifically, when the self-propelled lawn mower travels around a lawn along the boundary line for one circle, the boundary line is closed. At this time, a virtual channel is constructed through the second remote device (for example, remotely controlling the self-propelled lawn mower through a remote controller or an APP), and the self-propelled lawn mower is controlled through a control signal to go from the current lawn to the next lawn. On the new lawn, the self-propelled lawn mower can again autonomously identify the grass and non-grass areas and continue to construct the map of the working area. As Figure 5 shown is a schematic diagram of the movement scenario when the self-propelled lawn mower constructs the map of the working area, Figure 5 in the upper half of the movement scenario, the self-propelled lawn mower starts from point A on the left lawn, autonomously identifies the boundary line according to the image data and moves along the direction indicated by the arrow. When it returns to point A, the boundary line is closed. At this time, a virtual channel is constructed between point A and point B on the right lawn through the second remote device, and the self-propelled lawn mower is controlled through a control signal to go from point A on the current lawn to point B on the next lawn and continue to construct the map of the working area. Figure 5 in the lower half of the movement scenario, the self-propelled lawn mower starts from point C on the lawn, autonomously identifies the boundary line according to the image data and moves along the direction indicated by the arrow. When it returns to point C, the boundary line is closed. If it is determined that there is no other lawn to continue constructing, the autonomous construction of the map of the working area is completed.

[0065] In some embodiments, integrating the coordinate information of the movement route and the coordinate information of the boundary line to generate the boundary of the working area of the self-propelled lawn mower includes: If the coordinate information of the demarcation line is within a preset area, and the coordinate information of the moving route is included in the preset area, the working area boundary of the self-propelled lawn mower within the preset area is generated according to the coordinate information of the moving route.

[0066] Wherein, the preset area refers to an area with a complex environment. For example, the boundary area of a lawn with a complex surrounding environment, such as an area with a large number of obstacles such as trees and buildings, or a lawn that belongs to one's own family and the neighbor's family respectively and cannot be distinguished by grass and non-grass. At this time, the self-propelled lawn mower may not be able to completely identify the demarcation line autonomously. Therefore, the working area boundary within the preset area needs to be determined by the control signal sent by the second remote device.

[0067] Exemplarily, when encountering a complex environment, manual intervention is carried out to construct a map of the complex environment. After the construction is completed, the self-propelled lawn mower is switched back to the autonomous grass and non-grass recognition state. Manual intervention (such as remotely controlling the self-propelled lawn mower through a remote controller or an APP) helps the self-propelled lawn mower construct a map. When the map of the complex environment is constructed, the self-propelled lawn mower is switched back to the autonomous recognition state again.

[0068] Specifically, when it is detected that the self-propelled lawn mower is within the preset area, a request control message is sent to the second remote device. If the control signal sent by the second remote device is received, the moving route indicated by the control signal is calculated, the walking wheel assembly is controlled to make the self-propelled lawn mower travel along the moving route, and the coordinate information of the moving route is stored. The working area boundary of the self-propelled lawn mower within the preset area is generated according to the coordinate information of the moving route. If the control signal sent by the second remote device is not received within a preset time period, the demarcation line between grass and non-grass in the image data is identified based on deep learning, the walking wheel assembly is controlled to make the self-propelled lawn mower travel along the demarcation line, and the coordinate information of the demarcation line is stored. The working area boundary of the self-propelled lawn mower within the preset area is generated according to the coordinate information of the demarcation line.

[0069] In some embodiments, the self-propelled lawn mower further includes a memory for storing the coordinate information of the moving route, the coordinate information of the demarcation line, and the working area boundary.

[0070] After obtaining the coordinate information of the moving route, the coordinate information of the demarcation line, and the working area boundary, the information is stored in the memory for subsequent generation of the mowing map and information query.

[0071] In some embodiments, the self-propelled lawn mower sends the working area boundary to the second remote device through the wireless communication module.

[0072] After determining the boundary of the working area, send the boundary of the working area to the second remote device so that the user can view and confirm it in the second remote device. If it is determined that there is a problem with the boundary of the working area, reconstruct the area with problems.

[0073] In some embodiments, integrating the coordinate information of the moving route and the coordinate information of the demarcation line includes: Performing smoothing processing and hole filling processing on the coordinate information of the moving route and the coordinate information of the demarcation line.

[0074] Since the coordinate information of the moving route and the coordinate information of the demarcation line are obtained during the movement of the self-propelled lawn mower, there will be a certain degree of discontinuity. To ensure the continuity and smoothness of the finally generated boundary of the working area, smoothing processing and hole filling processing are performed on the coordinate information of the moving route and the coordinate information of the demarcation line.

[0075] When the mowing area is completely closed, an automatic generation of a boundary map of the mowing working area of the self-propelled lawn mower is performed according to the walking path information of the self-propelled lawn mower. The walking path information includes the coordinate information of the moving route and the coordinate information of the demarcation line. Exemplarily, when all the lawns have been closed by the walking path of the self-propelled lawn mower, an automatic generation of a boundary map of the mowing working area of the self-propelled lawn mower is performed by performing smoothing processing and hole filling processing according to the walking path. The boundary map of the working area can display information such as the walking path of the self-propelled lawn mower on each lawn and the order of mowing. According to the boundary map of the working area, the self-propelled lawn mower can autonomously perform the mowing task.

[0076] The beneficial effects of this embodiment: By visually identifying the demarcation line between grass and non-grass and combining the control signal of the second remote device, the construction of the mowing map of the self-propelled lawn mower is improved, and the construction efficiency and safety of the map construction are enhanced.

[0077] Figure 6 It is a schematic diagram of a method for building a boundary of a self-propelled lawn mower according to an embodiment of the present application. This embodiment is applicable to the situation of optimizing the determination of the mowing working area of the self-propelled lawn mower. This method can be executed by the boundary building device of the self-propelled lawn mower. The device can be implemented in a software and / or hardware manner and integrated in an electronic device; the electronic device involved in this embodiment can be a device with computing capabilities such as a server.

[0078] The self-propelled lawn mower includes a wireless communication module and a vision sensor. The method for building a boundary includes: Receiving a control signal sent by a second remote device through the wireless communication module; Obtaining image data around the self-propelled lawn mower through the vision sensor; Calculate the moving route indicated by the control signal, control the self-propelled mower to travel along the moving route, and store the coordinate information of the moving route; When the control signal is missing, identify the boundary between grass and non-grass in the image data, control the self-propelled mower to travel along the boundary, and store the coordinate information of the boundary; Integrate the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self-propelled mower.

[0079] In some embodiments, the second remote device is a mobile terminal.

[0080] In some embodiments, the wireless communication module includes at least one of the following: Bluetooth, WiFi, and cellular signal.

[0081] In some embodiments, the vision sensor includes a binocular camera.

[0082] In some embodiments, the self-propelled mower further includes a memory for storing the coordinate information of the moving route, the coordinate information of the boundary, and the working area boundary.

[0083] In some embodiments, the self-propelled mower sends the working area boundary to the second remote device through the wireless communication module.

[0084] In some embodiments, integrating the coordinate information of the moving route and the coordinate information of the boundary includes: Performing smoothing processing and hole filling processing on the coordinate information of the moving route and the coordinate information of the boundary.

[0085] In some embodiments, integrating the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self-propelled mower includes: If the coordinate information of the boundary is within a preset area and the preset area includes the coordinate information of the moving route, then generate the working area boundary of the self-propelled mower within the preset area according to the coordinate information of the moving route.

[0086] In some embodiments, the self-propelled mower further includes a differential positioning unit for acquiring the coordinate information.

[0087] In some embodiments, the self-propelled mower further includes a sensor assembly for acquiring the coordinate information.

[0088] The edge-building method of the self-propelled lawn mower provided by the embodiments of the present application can execute any of the method embodiments configured by the controller in the self-propelled lawn mower provided by the previous embodiment of the present application, and has corresponding functional modules and beneficial effects.

[0089] The embodiment of the present application is another type of self-propelled lawn mower, which can be combined with the self-propelled lawn mower in the above embodiment. The schematic diagram of the self-propelled lawn mower is as Figure 1 shown. This embodiment is applicable to the situation of optimizing the working mode of the self-propelled lawn mower. The working mode includes a positioning fusion algorithm or path planning. The optimization of the working mode of the self-propelled lawn mower is executed by the controller in the self-propelled lawn mower, and this device can be implemented in software and / or hardware.

[0090] The self-propelled lawn mower includes a body and a walking wheel assembly, and the walking wheel assembly is configured to support the body. Among them, the body of the self-propelled lawn mower refers to the hardware part for realizing the lawn mowing function, and the walking wheel assembly refers to the component for supporting the automatic walking of the self-propelled lawn mower.

[0091] The self-propelled lawn mower further includes a signal receiving unit configured to receive a signal sent by a first remote device, and the signal is used to determine the position of the self-propelled lawn mower. The signal receiving unit refers to the unit configured in the self-propelled lawn mower for receiving the position of the self-propelled lawn mower sent by an external first remote device. Specifically, the first remote device obtains the position information of the self-propelled lawn mower in real time, and sends a signal to the signal receiving unit in the self-propelled lawn mower according to this position information. After the signal receiving unit receives the signal sent by the first remote device, it processes the signal to obtain the position of the self-propelled lawn mower. The position of the self-propelled lawn mower is the position information obtained by relying on the first remote device outside the lawn mower, such as GPS positioning data, etc.

[0092] In some embodiments, the signal receiving unit is a Global Navigation Satellite System (GNSS) receiver. GNSS (Global Navigation Satellite System) is a navigation system that operates jointly using multiple satellites, ground receivers, and related devices. It can determine geographical location, speed, time, and other information by receiving signals from satellites. GNSS mainly consists of several major systems such as the Global Positioning System (GPS), Galileo, GLONASS, and BeiDou Navigation System. The goal of these systems is to provide high-precision navigation positioning and assisted navigation services globally.

[0093] Specifically, a Global Navigation Satellite System (GNSS) receiver is configured in the self-propelled lawn mower to receive satellite signals and determine the external positioning data of the self-propelled lawn mower according to the satellite signals.

[0094] In some embodiments, the signal receiving unit is a differential positioning unit, and the position of the self - moving lawn mower is the differential positioning result of the self - moving lawn mower.

[0095] The differential positioning unit refers to an internal device of the self - moving lawn mower that determines external positioning data through the differential positioning method. Then, the position of the self - moving lawn mower obtained by performing the differential positioning method on the signal through the differential positioning unit is the differential positioning result. Specifically, the signal receiving unit obtains RTK (Real - time kinematic) positioning data as the position of the self - moving lawn mower through the RTK method. RTK is a measurement method that can obtain centimeter - level positioning accuracy in the field in real time.

[0096] The self - moving lawn mower further includes a vision sensor for acquiring image data around the self - moving lawn mower. A vision sensor is deployed on the self - moving lawn mower to be able to acquire image data around the self - moving lawn mower in real time when the self - moving lawn mower is moving. In some embodiments, the vision sensor includes a binocular camera. The self - moving lawn mower obtains image data around through the binocular camera to improve the coverage of the image data.

[0097] The self - moving lawn mower further includes a controller electrically connected to the signal receiving unit and the vision sensor respectively; the signal quality adjustment method configured by the controller is as Figure 7 shown, and the specific process includes: S31. Receive the image data from the vision sensor; S32. Judge the signal quality of each area in the image data through a target detection algorithm; S33. Adjust the positioning fusion algorithm or perform path planning according to the signal quality of each area.

[0098] In some embodiments, judging the signal quality of each area in the image data through a target detection algorithm includes: Detecting obstacles through the target detection algorithm, and judging the signal quality of each area in the image data according to the number, volume, and / or height of the obstacles.

[0099] Since a large - area and low - height obstacle environment will have a great impact on the signals received by the signal receiving unit, in order to ensure the accuracy of determining the position of the self - moving lawn mower using the signals sent by the first remote device received, it is necessary to ensure the signal quality first. Specifically, the signals received by the signal receiving unit may include satellite signals and radio signals from the RTK base station, and both of these two signals are greatly affected by obstacles.

[0100] The environmental image data is acquired by using a vision sensor, and the features of the shelter are identified through an object detection algorithm in image processing technology, and information such as the volume, height, quantity, and coverage area of the shelter is extracted. The object detection algorithm can be implemented through steps such as image segmentation, edge detection, and feature extraction, which are common technical means for those skilled in the art, and the detailed algorithm will not be elaborated here.

[0101] According to the extracted shelter parameters, such as quantity, volume, and / or height, it is determined whether the shelter may affect the signal reception of the signal receiving unit. If the shelter is large or high, it may block satellite signals; if the shelter has a large coverage area, it may affect the signal propagation. Therefore, the signal quality of each area in the image data is judged according to the quantity, volume, and / or height of the shelter. Exemplarily, a mapping relationship between different range intervals of the quantity, volume, and / or height of the shelter and the signal quality is established in advance, and based on this mapping relationship, the corresponding signal quality can be found according to the quantity, volume, and / or height of the shelter in each area. The level correspondence in the specific mapping relationship can be determined according to the actual scenario and is not limited here.

[0102] In some embodiments, adjusting the positioning fusion algorithm according to the signal quality of each area includes: If the signal quality of the target area is less than the preset signal threshold, the fusion weight of the satellite positioning method in the positioning fusion algorithm is reduced.

[0103] Since the signal is the result of the signal receiving unit receiving the signal sent by the first remote device, and this signal is used to determine the position of the self-propelled lawn mower. If the signal quality in the target area is less than the preset signal threshold, it means that the result of signal reception in this area may be inaccurate. Therefore, if the position of the self-propelled lawn mower is determined solely based on the signal, the position determination will be inaccurate. If the position of the self-propelled lawn mower is determined based on the positioning fusion algorithm, in order to ensure the accuracy of the fusion positioning result, it is necessary to reduce the fusion weight of determining the position information according to the signal.

[0104] Exemplarily, the position determination method of the self-propelled lawn mower adopts a positioning fusion algorithm. The positioning fusion algorithm can adopt the multi-sensor fusion algorithm in the above embodiments, or fuse the satellite positioning method and other sensor positioning methods. If the signal quality of the target area is less than the preset signal threshold, the fusion weight of the satellite positioning method in the positioning fusion algorithm is reduced, and the fusion weight of other sensor positioning methods is increased. The specific reduction ratio can be determined according to the actual scenario and is not limited here.

[0105] In some embodiments, the positioning fusion algorithm further includes a positioning method using at least one of the data of vision, lidar, radar, wheel speedometer, and IMU.

[0106] Other sensor positioning methods in the positioning fusion algorithm adopt a positioning method using at least one of the data of vision, lidar, radar, wheel speedometer, and IMU.

[0107] In some embodiments, path planning is performed according to the signal quality of each region, including: If the self-propelled lawn mower enters the target region and the signal quality of the target region is less than the preset signal threshold, the path is adjusted to control the self-propelled lawn mower to drive away from the target region and enter another region where the signal quality is greater than or equal to the preset signal threshold.

[0108] When the self-propelled lawn mower enters a target region with a signal quality less than the preset signal threshold, in order to ensure the safety of the self-propelled lawn mower, it is necessary to control the self-propelled lawn mower to drive away from the target region as soon as possible and enter another region with a higher signal quality, that is, enter another region where the signal quality is greater than or equal to the preset signal threshold. In one embodiment, in order to ensure the mowing coverage rate in the region with poor signal quality, a suitable path can be planned to repeatedly enter and exit the region with poor signal and the region with good signal alternately, reducing the continuous working time in the region with poor signal. For example, enter the region with poor signal perpendicular to the long side of the region with poor signal and perform zigzag cutting.

[0109] Exemplarily, when the self-propelled lawn mower works at night, since the vision sensor cannot accurately identify the shelter, the self-propelled lawn mower needs to avoid the target region with poor signal quality performance and adopt corresponding obstacle avoidance strategies to ensure the safety of the self-propelled lawn mower.

[0110] In some embodiments, the positioning fusion algorithm is adjusted or path planning is performed according to the signal quality of each region, including: Generating a signal global map according to the signal quality of each region; Adjusting the positioning fusion algorithm or performing path planning according to the signal global map.

[0111] Combined with the vision sensor to analyze the occlusion parameters of the shelter, determine the signal quality of the signal received by the signal receiving unit itself, and mark the signal quality performance of the current map traveled by the self-propelled lawn mower according to the signal quality to obtain a signal global map carrying the signal quality of each region, that is, the RTK working condition map.

[0112] Exemplarily, while obtaining signal positioning data, the RTK performance of the current map is marked by combining the analysis result of the occlusion by the shelter in the visual dimension. For example, it can be achieved by analyzing the error of the RTK positioning data and combining the height, quantity, and size of the shelter identified by vision. If the RTK positioning data has a large error, that is, the signal quality is poor, the target area is marked on the map so that the self-propelled lawn mower can adjust the positioning fusion algorithm or perform path planning according to the signal global map.

[0113] Exemplarily, the self-propelled lawn mower adopts corresponding obstacle avoidance strategies according to its own working conditions and RTK performance marks. For example, at night, since the visual sensor may not be able to accurately identify the shelter, the self-propelled lawn mower needs to avoid the areas with poor RTK performance marks. When the RTK working condition is poor, the positioning fusion algorithm can be performed to reduce the weight of the satellite positioning result and increase the weight of the positioning data of other sensors to improve the overall positioning accuracy and reliability. Figure 8 It is a schematic diagram of a signal quality determination method configured by a controller on a self-propelled lawn mower according to an embodiment of the present application.

[0114] In some embodiments, the self-propelled lawn mower further includes a memory for storing a signal global map variable generated according to the signal quality of each region.

[0115] After generating the signal global map according to the signal quality of each region, the signal global map is stored in the memory as variable data. Exemplarily, during a period with good visual information, such as during the day, the signal global map is dynamically adjusted according to the image data collected by the self-propelled lawn mower in real time; during a period with poor visual information, such as at night, the positioning fusion algorithm is adjusted or path planning is performed according to the signal global map stored in the memory.

[0116] The beneficial effects of this embodiment: Based on the dual judgments of visual recognition and signal quality, the positioning fusion algorithm of the self-propelled lawn mower is adjusted or path planning is performed to guide the self-propelled lawn mower to perform the mowing task safely and efficiently. According to the RTK working condition map, a more robust adjustment of the positioning fusion algorithm and path adjustment of the self-propelled lawn mower are carried out, improving the mowing efficiency and safety of the self-propelled lawn mower.

[0117] The embodiment of the present application is another self-propelled lawn mower, which can be combined with the self-propelled lawn mower in the above embodiment. The schematic diagram of the self-propelled lawn mower is as Figure 1 shown. This embodiment is applicable to the situation of optimizing the power supply of multiple sensors of the self-propelled lawn mower. The optimization of the power supply of multiple sensors is executed by the controller in the self-propelled lawn mower, and this device can be implemented in software and / or hardware.

[0118] The self - propelled lawn mower includes: a body and a walking wheel assembly. The walking wheel assembly is configured to support the body. Herein, the body of the self - propelled lawn mower refers to the hardware part for realizing the lawn mowing function, and the walking wheel assembly refers to the component for supporting the automatic walking of the self - propelled lawn mower.

[0119] The self - propelled lawn mower further includes a plurality of sensor components disposed on the body. The plurality of sensor components disposed on the body are used to support the self - propelled lawn mowing function of the self - propelled lawn mower, such as including positioning function or path planning function, etc. The power supply device on the body supplies power to each sensor component in the plurality of sensor components according to requirements to support the sensor component to execute corresponding functions.

[0120] The self - propelled lawn mower also includes a controller, which is electrically connected to the plurality of sensor components respectively. The controller selectively cuts off the power supply to the plurality of sensor components. Specifically, the controller determines at least one idle sensor component from the plurality of sensor components according to the current working state of the self - propelled lawn mower, and cuts off the power supply from the power supply device to the idle sensor component. Herein, the idle sensor component refers to the component that does not currently support the self - propelled lawn mowing function of the self - propelled lawn mower.

[0121] In some embodiments, the self - propelled lawn mower further includes a plurality of switching elements configured to connect or disconnect the electrical connection between the plurality of sensor components and the power supply device.

[0122] A switching element is included between the power supply device and each sensor component. When the switching element is in the on state, it connects the electrical connection between the sensor component corresponding to the switching element and the power supply device. When the switching element is in the off state, it disconnects the electrical connection between the sensor component corresponding to the switching element and the power supply device. Specifically, the controller is respectively connected to the plurality of switching elements and is configured to: selectively cut off the power supply from the power supply device to at least one of the plurality of sensor components by controlling the plurality of switching elements.

[0123] In some embodiments, the plurality of sensor components include at least three of a differential positioning unit, a camera, a lidar, a radar, a wheel speed meter, and an IMU.

[0124] In the above - mentioned embodiments, at least three of a differential positioning unit, a camera, a lidar, a radar, a wheel speed meter, and an IMU are included in the plurality of sensor components for multi - sensor fusion positioning of the self - propelled lawn mower, and the plurality of sensor components may further include devices supporting other functions.

[0125] In some embodiments, selectively cutting off the power supply from the power supply device to at least one of the plurality of sensor components includes: Selecting whether to cut off the power supply to the differential positioning unit according to the signal quality.

[0126] Among them, the differential positioning unit is configured to receive the signal sent by the first remote device to obtain the external positioning data of the self - propelled lawn mower. The signal quality refers to the signal quality of the signal sent by the first remote device received by the differential positioning unit.

[0127] Specifically, if the signal quality is lower than the preset signal threshold, the power supply to the differential positioning unit is cut off. Exemplarily, if the RTK signal is lower than the preset signal threshold, it indicates that the RTK working condition in the environment where the current self - propelled lawn mower is located is poor, and the determined external positioning data may have a large error. In order to improve the positioning accuracy and avoid using the external positioning data, the power supply to the differential positioning unit is selected to be cut off to ensure the power supply efficiency, avoid powering the sensor components that contribute less to the current self - propelled lawn mower, improve the power saving efficiency, and thus improve the battery life of the self - propelled lawn mower.

[0128] That is, when the working condition is not suitable for RTK positioning, relevant transmitting and receiving sensors such as RTK can be turned off.

[0129] In some embodiments, after selecting whether to cut off the power supply to the differential positioning unit according to the signal quality, the method further includes: Selecting whether to restore the power supply to the differential positioning unit according to the information of the first other sensor; wherein, the first other sensor includes at least one sensor other than the differential positioning unit among the multiple sensors.

[0130] If the data quality obtained by the first other sensor of the self - propelled lawn mower is low, in order to ensure the accuracy of the positioning result, the power supply to the differential positioning unit is selected to be restored. For example, if it is currently in a dark state, the information obtained by the camera is limited, and the power supply to the differential positioning unit is selected to be restored; or if the current self - propelled lawn mower is driving on a bumpy road, the information obtained by the wheel speedometer has a certain error, and the power supply to the differential positioning unit is selected to be restored. The specific restoration strategy can be determined according to the positioning fusion strategy, which is not limited here. That is, when other positioning methods are inaccurate, the power supply to the differential positioning unit is selected to be restored to ensure the accuracy of the positioning result.

[0131] In some embodiments, selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: Selecting whether to cut off the power supply to the camera according to the visual visibility information.

[0132] Among them, the camera is used to detect the environmental information around the self - propelled lawn mower to determine the visual positioning data through the environmental information. The visual visibility information refers to the number of environmental feature objects in the image data obtained by the camera.

[0133] Specifically, if the visually visible information is lower than a preset threshold, indicating that the number of environmental feature objects is small at present, there are certain errors and inaccuracies in positioning through environmental information, then the power supply to the camera is cut off. Exemplarily, if it is currently in a dark state, or there are few feature objects in the current image data, it means that the environment where the current self-propelled lawn mower is located is relatively monotonous, and the determined visual positioning data may have a large error. Therefore, in order to improve the positioning accuracy and avoid using visual positioning data, the power supply to the camera is selected to be cut off to ensure the power supply efficiency, avoid supplying power to the sensor components that contribute less to the current self-propelled lawn mower, improve the power saving efficiency, and thus improve the battery life of the self-propelled lawn mower.

[0134] That is, when there are few working condition feature objects and it is not conducive to visual positioning, the visual sensor can be turned off and the power supply to it can be stopped.

[0135] In some embodiments, after selecting whether to cut off the power supply to the camera according to the visually visible information, the method further includes: Selecting whether to resume the power supply to the camera according to the information of the second other sensors; wherein, the second other sensors include at least one sensor other than the camera among the multiple sensors.

[0136] If the data quality obtained by the second other sensors of the self-propelled lawn mower is low, in order to ensure the accuracy of the positioning result, the power supply to the camera is selected to be resumed. For example, if it is currently in an area where the signal is blocked by an obstacle, the signal quality obtained by the differential positioning unit is poor, and the power supply to the camera is selected to be resumed; or if the current self-propelled lawn mower is driving on a bumpy road surface, there are certain errors in the information obtained by the wheel speedometer, and the power supply to the camera is selected to be resumed. The specific resume strategy can be determined according to the positioning fusion strategy and is not limited herein. That is, when other positioning methods are inaccurate, the power supply to the camera is selected to be resumed to ensure the accuracy of the positioning result.

[0137] In some embodiments, selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: Selecting at least one target sensor component from the multiple sensor components to cut off the power supply according to the remaining power of the power supply device and the power of the multiple sensor components.

[0138] If the remaining power of the power supply device is less than a first preset power threshold, and this first power threshold is greater than the preset power threshold in the next embodiment, indicating that the power supply device is currently in a low power state but has not reached the recharge standard, then at least one high-power target sensor component is selected from the multiple sensor components to cut off the power supply according to the power of the multiple sensor components, so as to improve the subsequent battery life of the self-propelled lawn mower.

[0139] Exemplarily, if the remaining power of the power supply device is less than 50%, the multiple sensor components are sorted in descending order of power consumption, and the endurance of the power supply device after sequentially cutting off the target sensor component ranked first in the sorting order is calculated until the endurance reaches the preset standard, and the final target sensor component to be cut off is determined.

[0140] Exemplarily, when it is monitored that the self-propelled lawn mower is within the preset area range within the preset time period, indicating that the self-propelled lawn mower is in a trapped state, the self-propelled lawn mower enters the low-power mode and stops power supply to sensors such as cameras, differential positioning units, and odometers.

[0141] In some embodiments, selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: If the remaining power of the power supply device is less than the preset power threshold, at least one path planning associated sensor component is selected from the multiple sensor components according to the requirements of path planning, and the power supply to the non-path planning associated sensor components is cut off.

[0142] If the remaining power of the power supply device is low and needs to be recharged, in order to ensure smooth recharging, the power supply to the non-path planning associated sensor components is cut off, and only the sensor components related to path planning during recharging are powered.

[0143] Exemplarily, when the self-propelled lawn mower needs to be recharged due to low power and cannot continue to work, the power supply to the unnecessary sensor components can be cut off according to the characteristics of the planned path, so as to ensure that the remaining power can support the self-propelled lawn mower to return to the charging pile.

[0144] In some embodiments, selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: Select whether to cut off the power supply to the IMU according to the road surface bump information.

[0145] Wherein, the road surface bump information refers to the state information of the road surface where the self-propelled lawn mower is currently traveling, which can be determined by the image data obtained by the vision sensor deployed on the body of the self-propelled lawn mower, or by the vibration data obtained by the vibration sensor deployed on the body of the self-propelled lawn mower, or can be determined by other means, which is not limited herein.

[0146] If it is determined according to the road surface bump information that the bump degree of the road surface where the self-propelled lawn mower is currently traveling exceeds the threshold, and since the accuracy of the IMU will decrease on the bumpy road surface, resulting in a decrease in the reliability of the data obtained by the IMU, the power supply to the IMU is cut off.

[0147] Advantages of this embodiment: By monitoring different working condition tasks of the self-propelled lawn mower and selecting different sensor components for power supply according to different working conditions determined by the monitoring, the self-propelled lawn mower can complete the lawn mowing task more efficiently and for a longer time, thereby achieving the power-saving and endurance function of the self-propelled lawn mower.

[0148] The above shows and describes the basic principles, main features and advantages of this application. Those skilled in the art of this industry should understand that the above embodiments do not limit this application in any form. Any technical solutions obtained by means of equivalent replacement or equivalent transformation fall within the protection scope of this application.

Claims

1. A self - propelled lawn mower, comprising: A body; A walking wheel assembly configured to support the body; A signal receiving unit configured to receive a signal sent by a first remote device to obtain external positioning data of the self - propelled lawn mower; A first sensor assembly configured to detect environmental information around the self - propelled lawn mower; A second sensor assembly configured to detect the motion state of the self - propelled lawn mower itself; A fusion positioning unit disposed on the body and electrically connected to the signal receiving unit, the first sensor assembly, and the second sensor assembly, the fusion positioning unit being configured to: Locate the self - propelled lawn mower according to the environmental information and generate a first positioning result by fusing the external positioning data; Locate the self - propelled lawn mower according to the motion state and generate a second positioning result by fusing the external positioning data; Fuse the first positioning result and the second positioning result to generate a final positioning result.

2. The self-propelled lawn mower according to claim 1, characterized in that, The signal receiving unit is a Global Navigation Satellite System (GNSS) receiver.

3. The self-propelled lawn mower according to claim 2, characterized in that, The signal receiving unit is a differential positioning unit, and the external positioning data is the differential positioning result of the self - propelled lawn mower.

4. The self-propelled lawn mower according to claim 1, characterized in that, The first sensor assembly includes a camera assembly.

5. The self-propelled lawn mower according to claim 1, characterized in that, Locating the self - propelled lawn mower according to the environmental information includes: Locating the self - propelled lawn mower based on VSLAM according to the environmental information.

6. The self-propelled lawn mower according to claim 1, characterized in that, The second sensor assembly at least includes a wheel speed meter.

7. The self-propelled lawn mower according to claim 6, wherein, The second sensor assembly further includes an IMU.

8. The self-propelled lawn mower according to claim 1, wherein, Locating the self - propelled lawn mower according to the environmental information and generating a first positioning result by fusing the external positioning data includes: Locating the self - propelled lawn mower according to the environmental information and generating a first positioning result by fusing the external positioning data through Kalman filtering.

9. The self-propelled lawn mower according to claim 1, wherein, Locating the self - propelled lawn mower according to the motion state and generating a second positioning result by fusing the external positioning data includes: Locating the self - propelled lawn mower according to the motion state and generating a second positioning result by fusing the external positioning data through Kalman filtering.

10. The self-propelled lawn mower according to claim 1, characterized in that, Fusing the first positioning result and the second positioning result to generate a final positioning result includes: Adjusting the fusion weight of the first positioning result and the second positioning result according to the visual positioning quality and / or the quality of the signal; Fusing the first positioning result and the second positioning result according to the fusion weight to generate a final positioning result.

11. A self - propelled lawn mower, comprising: A body; A walking wheel assembly configured to support the body; A wireless communication module configured to communicate with a second remote device, including receiving a control signal sent by the second remote device; A vision sensor for acquiring image data around the self - propelled lawn mower; A controller electrically connected to the wireless communication module and the vision sensor respectively, acquiring the control signal and the image data; Characterized in that the controller is configured to: Calculate a moving route indicated by the control signal, control the walking wheel assembly to make the self - propelled lawn mower travel along the moving route, and store coordinate information of the moving route; Based on deep learning, identify the boundary between grass and non-grass in the image data, control the walking wheel assembly to make the self-propelled lawn mower travel along the boundary, and store the coordinate information of the boundary; Integrate the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self-propelled lawn mower.

12. The self-propelled lawn mower according to claim 11, characterized in that, The second remote device is a mobile terminal.

13. The self-propelled lawn mower according to claim 11, characterized in that, The wireless communication module includes at least one of the following: Bluetooth, WiFi, and cellular signal.

14. The self-propelled lawn mower according to claim 11, wherein, The vision sensor includes a binocular camera.

15. The self-propelled lawn mower according to claim 11, characterized in that, The self-propelled lawn mower further includes a memory for storing the coordinate information of the moving route, the coordinate information of the boundary, and the working area boundary.

16. The self-propelled lawn mower according to claim 11, characterized in that, The self-propelled lawn mower sends the working area boundary to the second remote device through the wireless communication module.

17. The self-propelled lawn mower according to claim 11, wherein, Integrating the coordinate information of the moving route and the coordinate information of the boundary includes: Perform smoothing processing and hole filling processing on the coordinate information of the moving route and the coordinate information of the boundary.

18. The self-propelled lawn mower according to claim 11, wherein, Integrating the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self-propelled lawn mower includes: If the coordinate information of the boundary is within a preset area and the preset area includes the coordinate information of the moving route, then generate the working area boundary of the self-propelled lawn mower within the preset area according to the coordinate information of the boundary and the coordinate information of the moving route.

19. The self-propelled lawn mower according to claim 11, characterized in that, The self-propelled lawn mower further includes a differential positioning unit for acquiring the coordinate information.

20. A method for building a boundary of a self-propelled lawn mower, the self-propelled lawn mower includes a wireless communication module and a vision sensor, and the method for building a boundary includes: Receive a control signal sent by a second remote device through the wireless communication module; Acquire the image data around the self-propelled lawn mower through the vision sensor; Calculate the moving route indicated by the control signal, control the self-propelled lawn mower to travel along the moving route, and store the coordinate information of the moving route; When the control signal is missing, identify the boundary between grass and non-grass in the image data, control the self-propelled lawn mower to travel along the boundary, and store the coordinate information of the boundary; Integrate the coordinate information of the moving route and the coordinate information of the boundary to generate the working area boundary of the self-propelled lawn mower.

21. A self-propelled lawn mower, including: A fuselage; A walking wheel assembly configured to support the fuselage; A signal receiving unit configured to receive a signal sent by a first remote device, and the signal is used to determine the position of the self-propelled lawn mower; A vision sensor for acquiring the image data around the self-propelled lawn mower; A controller electrically connected to the signal receiving unit and the vision sensor respectively; Characterized in that the controller is configured to: Receive the image data from the vision sensor; Judge the signal quality of each area in the image data through a target detection algorithm; Adjust the positioning fusion algorithm or perform path planning according to the signal quality of each area.

22. The self-propelled lawn mower according to claim 21, wherein, The signal receiving unit is a Global Navigation Satellite System GNSS receiver.

23. The self-propelled lawn mower according to claim 22, wherein, The signal receiving unit is a differential positioning unit, and the position of the self-propelled lawn mower is the differential positioning result of the self-propelled lawn mower.

24. The self-propelled lawn mower according to claim 21, characterized in that, The vision sensor includes a binocular camera.

25. The self-propelled lawn mower according to claim 21, wherein, By using a target detection algorithm, the signal quality of each region in the image data is judged, including: Detecting obstacles through the target detection algorithm, and judging the signal quality of each region in the image data according to the number, volume and / or height of the obstacles.

26. The self-propelled lawn mower according to claim 21, characterized in that, Adjusting the positioning fusion algorithm according to the signal quality of each region, including: If the signal quality of the target region is less than the preset signal threshold, the fusion weight of the satellite positioning method in the positioning fusion algorithm is reduced.

27. The self-propelled lawn mower according to claim 26, characterized in that, The positioning fusion algorithm further includes a positioning method using at least one of the data of vision, lidar, radar, wheel speedometer and IMU.

28. The self-propelled lawn mower according to claim 21, wherein, Performing path planning according to the signal quality of each region, including: If the self-propelled lawn mower enters the target region and the signal quality of the target region is less than the preset signal threshold, the path is adjusted to control the self-propelled lawn mower to drive out of the target region and enter other regions where the signal quality is greater than or equal to the preset signal threshold.

29. The self-propelled lawn mower according to claim 21, wherein, Adjusting the positioning fusion algorithm or performing path planning according to the signal quality of each region, including: Generating a signal global map according to the signal quality of each region; Adjusting the positioning fusion algorithm or performing path planning according to the signal global map.

30. The self-propelled lawn mower according to claim 29, characterized in that, The self-propelled lawn mower further includes a memory for storing a signal global map variable generated according to the signal quality of each region.

31. A self-propelled lawn mower, comprising: A fuselage; A traveling wheel assembly configured to support the fuselage; A plurality of sensor assemblies disposed on the fuselage; A controller electrically connected to the plurality of sensor assemblies respectively; A power supply device disposed on the fuselage and configured to supply power to the controller and the plurality of sensor assemblies; Characterized in that the controller is configured to: Selectively cut off the power supply of the power supply device to at least one of the plurality of sensor assemblies.

32. The self-propelled lawn mower according to claim 31, characterized in that, The self-propelled lawn mower further includes a plurality of switching elements configured to connect or disconnect the electrical connection between the plurality of sensor assemblies and the power supply device.

33. The self-propelled lawn mower according to claim 31, characterized in that, The plurality of sensor assemblies include at least three of a differential positioning unit, a camera, a lidar, a radar, a wheel speedometer and an IMU.

34. The self-propelled lawn mower according to claim 31, characterized in that, Selectively cutting off the power supply of the power supply device to at least one of the plurality of sensor assemblies includes: Selecting whether to cut off the power supply to the differential positioning unit according to the signal quality.

35. The self-propelled lawn mower according to claim 34, wherein, After selecting whether to cut off the power supply to the differential positioning unit according to the signal quality, the method further includes: Selecting whether to resume the power supply to the differential positioning unit according to the information of the first other sensor; wherein the first other sensor includes at least one sensor other than the differential positioning unit among the plurality of sensors.

36. The self-propelled lawn mower according to claim 33, characterized in that, Selectively cutting off the power supply of the power supply device to at least one of the plurality of sensor assemblies includes: Selecting whether to cut off the power supply to the camera according to the visual visibility information.

37. The self-propelled lawn mower according to claim 36, characterized in that, After selecting whether to cut off the power supply to the camera according to the visual visibility information, the method further includes: Select whether to resume power supply to the camera according to the information of the second other sensor; wherein, the second other sensor includes at least one sensor other than the camera among the multiple sensors.

38. The self-propelled lawn mower according to claim 31, characterized in that, Selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: Selecting at least one target sensor component from the multiple sensor components to cut off the power supply according to the remaining power of the power supply device and the power of the multiple sensor components.

39. The self-propelled lawn mower according to claim 31, wherein, Selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: If the remaining power of the power supply device is less than a preset power threshold, select at least one path planning associated sensor component from the multiple sensor components according to the requirements of path planning, and cut off the power supply to the non-path planning associated sensor components.

40. The self-propelled lawn mower according to claim 33, characterized in that, Selectively cutting off the power supply of the power supply device to at least one of the multiple sensor components includes: Select whether to cut off the power supply to the IMU according to the road surface bump information.

Images