Self-propelled lawn mower, and boundary establishment method for self-propelled lawn mower

Abstract

A self-propelled lawn mower, and a boundary establishment method for the self-propelled lawn mower. The self-propelled lawn mower at least comprises: a body; a traveling wheel assembly, which is configured to support the body; a signal receiving unit, which is configured to receive a signal sent by a first remote device, so as to obtain external positioning data of the self-propelled lawn mower; a first sensor assembly, which is configured to detect surrounding environment information of the self-propelled lawn mower; a second sensor assembly, which is configured to detect a motion state of the self-propelled lawn mower; and a fusion positioning unit, which is configured to position the self-propelled lawn mower on the basis of the environment information and fuse the external positioning data so as to generate a first positioning result, position the self-propelled lawn mower on the basis of the motion state and fuse the external positioning data so as to generate a second positioning result, and fuse the first positioning result and the second positioning result so as to generate a final positioning result.

Description

Self-moving lawn mower and edging method for self-moving lawn mower

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on January 26, 2024, with application number 202410114668.2, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to a lawn mower, for example, to a self-propelled lawn mower and an edge building method for the self-propelled lawn mower. Background Art

[0003] When a lawn mower is mowing the lawn, it needs to ensure accurate positioning results to ensure mowing efficiency. Therefore, it is difficult to ensure the accuracy of positioning results based on a single sensor alone. It is necessary to further improve the accuracy of positioning results of autonomous lawn mowers.

[0004] Furthermore, the lawn mower needs to construct a mowing map when performing self-moving mowing. However, in the related art, the construction of the mowing map relies on manual control of the lawn mower, resulting in low efficiency and difficulty in ensuring safety.

[0005] When a lawn mower is mowing the lawn, the presence of environmental obstructions 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 endurance of the lawn mower.

[0006] This section provides background information related to the present application which is not necessarily prior art. Summary of the Invention

[0007] An object of the present application is to solve or at least alleviate a part or all of the above problems. To this end, an object of the present application is to provide a self-propelled lawn mower and an edge building method for the self-propelled lawn mower.

[0008] In order to achieve the above objectives, this application adopts the following technical solutions:

[0009] A self-propelled lawn mower comprises: 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 arranged 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 fuse the external positioning data to generate a first positioning result; locate the self-propelled lawn mower according to the motion state, and fuse the external positioning data to generate a second positioning result; and fuse the first positioning result and the second positioning result to generate a final positioning result.

[0010] A self-moving lawn mower comprises: a body; a travel 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 visual sensor configured to acquire image data of the self-moving lawn mower's periphery; a controller electrically connected to the wireless communication module and the visual sensor, respectively, to acquire the control signal and the image data; wherein the controller is configured to: calculate a moving route indicated by the control signal, control the travel wheel assembly to make the self-moving lawn mower move along the moving route, and store coordinate information of the moving route; identify a boundary between grass and non-grass in image data based on deep learning, control the travel wheel assembly to make the self-moving lawn mower move along the dividing line, and store the coordinate information of the dividing line; and integrate the coordinate information of the moving route and the coordinate information of the dividing line to generate a working area boundary of the self-moving lawn mower.

[0011] A method for establishing a boundary for a self-moving lawn mower, the self-moving lawn mower including a wireless communication module and a visual sensor, the method comprising: receiving a control signal sent by a second remote device via the wireless communication module; acquiring image data of the surrounding area of ​​the self-moving lawn mower via the visual sensor; calculating a moving route indicated by the control signal, controlling the self-moving lawn mower to move along the moving route, and storing coordinate information of the moving route; when the control signal is absent, identifying a boundary between grass and non-grass in the image data, controlling the self-moving lawn mower to move along the dividing line, and storing coordinate information of the dividing line; and integrating the coordinate information of the moving route and the coordinate information of the dividing line to generate a working area boundary for the self-moving lawn mower.

[0012] A self-propelled lawn mower comprises: 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, the signal being used to determine the position of the self-propelled lawn mower; a visual sensor configured to acquire image data of the periphery of the self-propelled lawn mower; and a controller electrically connected to the signal receiving unit and the visual sensor, respectively; wherein the controller is configured to: receive image data from the visual sensor; determine the signal quality of each area in the image data through a target detection algorithm; and adjust a positioning fusion algorithm or perform path planning based on the signal quality of each area.

[0013] A self-propelled lawn mower comprises: a body; a travel wheel assembly configured to support the body; a plurality of sensor assemblies disposed on the body; a controller electrically connected to the plurality of sensor assemblies; and a power supply device disposed on the body and configured to supply power to the controller and the plurality of sensor assemblies; wherein 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.

[0014] The benefits of this application are as follows: 1) By fusing external positioning data with environmental information and motion state positioning, and then further fusing the fusion results for final positioning, the positioning error caused by the accumulation of a single irregular environment through visual features and the positioning error caused by a single inaccurate ground state to the motion state are avoided, and multiple sensor data are effectively integrated to improve the positioning accuracy of the self-propelled lawn mower. 2) By visually identifying the boundary between grass and non-grass and combining it with the control signal of a second remote device, a mowing map is constructed for the self-propelled lawn mower, thereby improving the efficiency of mowing map construction 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 path planning is performed to guide the self-propelled lawn mower to perform mowing tasks safely and efficiently. The positioning fusion algorithm is adjusted more robustly according to the RTK working condition map, and the path of the self-propelled lawn mower is adjusted, thereby improving the mowing efficiency and safety of the self-propelled lawn mower. 4) By monitoring different working conditions of the self-propelled lawn mower, different sensor components are selected for power supply according to the different working conditions determined by the monitoring, so that the self-propelled lawn mower can complete the mowing task more efficiently and for a longer time, thereby achieving the power saving and endurance function of the self-propelled lawn mower. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG1 is a schematic diagram of a self-propelled lawn mower according to an embodiment of the present application;

[0016] FIG2 is a schematic diagram of a flow chart of a fusion positioning process of a fusion positioning unit configuration according to an embodiment of the present application;

[0017] FIG3 is a schematic diagram of the architecture of a fusion positioning unit configuration method according to an embodiment of the present application;

[0018] FIG4 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;

[0019] FIG5 is a schematic diagram of a moving scene when a self-propelled lawn mower constructs a work area map according to an embodiment of the present application;

[0020] FIG6 is a schematic diagram of an edge building method of a self-propelled lawn mower according to an embodiment of the present application;

[0021] FIG7 is a signal quality adjustment method of a controller configuration according to an embodiment of the present application;

[0022] FIG8 is a schematic diagram of a signal quality determination method for a controller configuration on a self-propelled lawn mower according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] Before any embodiments of the present application are explained in detail, it is to be understood that the application is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the foregoing drawings.

[0024] In this application, the terms "comprises," "includes," "has," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0025] In this application, the term "and / or" describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " in this application generally indicates that the related objects are in an "and / or" relationship.

[0026] In this application, the terms "connect," "combine," "couple," and "install" may refer to direct connection, combination, coupling, or installation, or indirect connection, combination, coupling, or installation. For example, a direct connection refers to two parts or components being connected together without an intermediary, and an indirect connection refers to two parts or components being connected to at least one intermediary, with the two parts or components being connected via the intermediary. Furthermore, "connect" and "couple" are not limited to physical or mechanical connections or couplings and may include electrical connections or couplings.

[0027] In this application, it will be understood by those skilled in the art that relative terms (e.g., "about," "approximately," "substantially," etc.) used in conjunction with quantities or conditions include the values ​​and have the meaning indicated by the context. For example, the relative terms include at least the degree of error associated with the measurement of a specific value, the tolerance caused by manufacturing, assembly, use, etc. associated with a specific value. Such terms should also be considered to disclose a range defined by the absolute values ​​of the two endpoints. Relative terms may refer to plus or minus a certain percentage (e.g., 1%, 5%, 10% or more) of the indicated value. Numerical values ​​that do not use relative terms should also be disclosed as specific values ​​with tolerances. In addition, "substantially" may refer to plus or minus a certain degree (e.g., 1 degree, 5 degrees, 10 degrees or more) on the basis of the indicated angle when expressing a relative angular position relationship (e.g., substantially parallel, substantially perpendicular).

[0028] In this application, it will be understood by those skilled in the art that the function performed by an assembly can be performed by one assembly, multiple assemblies, one part, or multiple parts. Similarly, the function performed by a part can also be performed by one part, one assembly, or a combination of multiple parts.

[0029] In the present application, the terms "upper", "lower", "left", "right", "front", "back" and other directional words are described based on the orientation and positional relationship shown in the accompanying drawings, and should not be understood as limiting the embodiments of the present application. In addition, in the context, it is also necessary to understand that when it is mentioned that an element is connected to another element "upper" or "lower", it can not only be directly connected to the other element "upper" or "lower", but also be indirectly connected to the other element "upper" or "lower" through an intermediate element. It should also be understood that directional words such as upper side, lower side, left side, right side, front side, back side, etc. not only represent the positive orientation, but can also be understood as the lateral orientation. For example, below can include directly below, lower left, lower right, lower front and lower back, etc.

[0030] In this application, the terms "controller," "processor," "central processing unit," "CPU," and "MCU" are used interchangeably. Where a unit "controller," "processor," "central processing unit," "CPU," or "MCU" is used to perform a particular function, unless otherwise specified, the function may be performed by a single unit or multiple units.

[0031] In this application, the terms "device", "module" or "unit" can be implemented in the form of hardware or software to achieve specific functions.

[0032] In this application, the terms "calculate", "judge", "control", "determine", "identify", etc. refer to the operations and processes of a computer system or similar electronic computing device (e.g., controller, processor, etc.).

[0033] Figure 1 is a schematic diagram of a self-propelled lawn mower according to an embodiment of the present application, comprising a laser radar 1, a first sensor assembly 2, a wireless communication module 3, a signal receiving unit 4, a travel wheel assembly 5, and a working assembly 6. The first sensor assembly 2 is configured to detect environmental information surrounding the self-propelled lawn mower. In one embodiment, the first sensor assembly 2 includes a visual sensor, such as a camera assembly. The wireless communication module 3, such as a Bluetooth module, a cellular network module, or a WiFi module, is used by the lawn mower to communicate with other remote devices. The signal receiving unit 4 is configured to receive positioning signals, such as a GNSS receiver or a differential positioning unit. The travel wheel assembly 5 is configured to drive the self-propelled lawn mower to move. The working assembly 6 is configured to support the primary operating functions of the self-propelled lawn mower, such as a cutter disc for mowing. This embodiment is applicable to situations where the positioning accuracy of the self-propelled lawn mower needs to be optimized. This optimization is performed by a fusion positioning unit 7 in the self-propelled lawn mower, which can be implemented as a controller.

[0034] The self-propelled lawn mower comprises a body, and a travel wheel assembly 5 is configured to support the body. The self-propelled lawn mower body refers to a hardware part for realizing the mowing function, and the travel wheel assembly refers to a component for supporting the self-propelled lawn mower to move automatically.

[0035] The self-moving lawn mower also includes a signal receiving unit 4, which is configured to receive a signal sent by a first remote device to obtain external positioning data of the self-moving lawn mower. Specifically, after receiving the signal sent by the first remote device, the signal receiving unit 4 processes the signal to obtain external positioning data. The external positioning data refers to the location information obtained by the self-moving lawn mower based on the first remote device outside the lawn mower, such as GPS positioning data. Exemplarily, the first remote device is a satellite. After the signal receiving unit receives the signal transmitted by the satellite, it calculates the signal transmission time based on the signal transmission time and the local time, and then obtains the satellite-device distance in combination with the speed of light, and then determines the location information based on the satellite-device distance.

[0036] 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 utilizes multiple satellites, ground-based receivers, and related equipment. It can determine information such as geographic location, speed, and time by receiving signals from satellites. GNSS is primarily composed of several major systems, including the Global Positioning System (GPS), Galileo, GLONASS, and the BeiDou Navigation System. These systems aim to provide high-precision navigation and positioning and assisted navigation services worldwide.

[0037] Specifically, the self-propelled lawn mower is configured with a global navigation satellite system (GNSS) receiver to receive satellite signals and determine external positioning data of the self-propelled lawn mower based on the satellite signals.

[0038] In some embodiments, the signal receiving unit 4 is a differential positioning unit, and the external positioning data is a differential positioning result of the self-propelled lawn mower.

[0039] The differential positioning unit is an internal device within the self-propelled lawn mower that determines external positioning data using differential positioning methods. The differential positioning unit then processes the signal to obtain external positioning data, which is the differential positioning result. Specifically, the signal receiving unit uses RTK (Real-time Kinematic) positioning data as external positioning data. RTK is a measurement method that can achieve centimeter-level positioning accuracy in real time in the field.

[0040] The self-moving lawn mower further comprises a first sensor assembly 2 configured to detect environmental information around the self-moving lawn mower. In some embodiments, the first sensor assembly 2 comprises a camera assembly.

[0041] The first sensor assembly 2 is configured with a camera assembly to detect environmental information surrounding the self-propelled lawn mower. Specifically, the first sensor assembly 2 is configured to obtain visual dimension information, detect environmental information surrounding the self-propelled lawn mower using the visual dimension information, and determine visual positioning data in the visual dimension using the visual dimension information. Specifically, the camera assembly includes a binocular camera, etc.

[0042] The self-moving lawn mower further comprises a second sensor assembly 8 configured to detect the motion state of the self-moving lawn mower itself. In some embodiments, the second sensor assembly 8 comprises at least a wheel speed meter.

[0043] The second sensor assembly 8 detects the motion state of the self-propelled lawn mower itself by configuring a wheel speed meter, which is used to obtain the speed information of the wheels in the travel wheel assembly of the self-propelled lawn mower and determine the motion positioning data of the self-propelled lawn mower through the wheel speed information.

[0044] In some embodiments, the second sensor assembly 8 further includes an IMU.

[0045] Specifically, motion information can be obtained through the wheel speed meter in the second sensor component 8, and 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 component 8, that is, the motion positioning data is determined by combining the data obtained by the wheel speed meter and the IMU.

[0046] The self-propelled lawn 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. A flow chart of the fusion positioning process configured by the fusion positioning unit 7 is shown in FIG2 . The specific process includes:

[0047] S11. Positioning the autonomous lawn mower according to environmental information, and integrating external positioning data to generate a first positioning result.

[0048] S12: Position the self-propelled lawn mower according to the motion state, and fuse the external positioning data to generate a second positioning result.

[0049] S13: Fuse the first positioning result and the second positioning result to generate a final positioning result.

[0050] 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 status, and fuses these data to determine the final positioning result of the autonomous lawn mower. A schematic diagram of the configuration method of the fusion positioning unit is shown in Figure 3.

[0051] In some embodiments, S11 locates the self-propelled lawn mower according to the environmental information and integrates the external positioning data to generate a first positioning result, including:

[0052] The self-propelled lawn mower is positioned according to the environmental information, and the external positioning data is fused through Kalman filtering to generate a first positioning result.

[0053] Specifically, the environmental information includes image information acquired by the camera assembly, and the visual positioning data of the self-propelled lawn mower is determined based on the image information. The visual positioning data and the external positioning data are fused through Kalman filtering to generate a first positioning result.

[0054] Exemplarily, environmental information is acquired through a camera component to perform VSLAM positioning to obtain visual positioning data, and then a first positioning result based on vision is determined by fusing the VSLAM positioning data and the RTK external positioning data.

[0055] 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. The 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 accelerometer detects the acceleration signal of the object in the independent three axes of the carrier coordinate system, and the gyroscope detects the angular velocity signal of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and uses this to calculate the attitude of the object.

[0056] The first sensor assembly, consisting of a camera assembly and an IMU, uses the visual sensor to capture environmental information and combines it with the IMU to generate the autonomous mower's visual inertial odometry (VIO), which serves as visual positioning data. The VIO uses visual odometry to estimate the mower's pose from camera images and combines it with inertial measurements from the IMU to correct for errors caused by rapid motion due to poor image capture.

[0057] Exemplarily, environmental information is obtained through a camera component and fused with an IMU to obtain a visual inertial odometry (VIO) of the self-propelled lawn mower, and then the visual inertial odometry (VIO) and RTK external positioning data are fused to determine a first vision-based positioning result.

[0058] In some embodiments, S12 locates the self-propelled lawn mower according to the motion state and fuses the external positioning data to generate a second positioning result, including:

[0059] The self-propelled lawn mower is positioned according to the motion state, and the external positioning data is fused through Kalman filtering to generate a second positioning result.

[0060] Specifically, the motion state includes speed information acquired by the wheel speed meter. The motion positioning data of the self-moving lawn mower is determined based on this speed information. This motion positioning data is then fused with external positioning data using a Kalman filter to generate a second positioning result. The motion state includes speed information acquired by the wheel speed meter and inertial data acquired by the IMU. The motion positioning data is determined based on this speed information and inertial data. This motion positioning data is then fused with external positioning data using a Kalman filter to generate a second positioning result.

[0061] In some embodiments, S13 fuses the first positioning result and the second positioning result to generate a final positioning result, including:

[0062] Adjusting a fusion weight of the first positioning result and the second positioning result according to a visual positioning quality and / or a quality of the signal;

[0063] The first positioning result and the second positioning result are fused according to the fusion weight to generate a final positioning result.

[0064] The first positioning result is visual positioning data, whose accuracy depends on the quality of visual positioning. The second positioning result is motion positioning data, which integrates motion state and external positioning data. Due to the relative accuracy of motion state acquisition, the accuracy of the second positioning data mainly depends on the accuracy of external positioning data, that is, on the quality of the signal. Therefore, the fusion weight of the first and second positioning results is adjusted according to the quality of visual positioning and / or signal. The first and second positioning results are fused using Kalman filtering based on the fusion weight to obtain the final positioning result.

[0065] For example, if the visual positioning quality is greater than a first preset quality threshold, the fusion weight of the first positioning result is determined to be greater than the fusion weight of the second positioning result; if the signal quality is less than a preset signal threshold, the fusion weight of the first positioning result is determined to be greater than the fusion weight of the second positioning result; or if the visual positioning quality is less than a second preset quality threshold, the fusion weight of the first positioning result is determined to be less than the fusion weight of the second positioning result, and the first preset quality threshold is greater than the second preset quality threshold. Furthermore, the specific ratio of the fusion weights can be dynamically adjusted based on the specific conditions of the RTK signal quality and visual positioning quality in actual scenarios, and is not limited here.

[0066] The beneficial effects of this embodiment are as follows: by fusing external positioning data with environmental information and motion status positioning, and then further fusing the fusion results for final positioning, the positioning error caused by the accumulation of a single irregular environment through visual features, and the positioning error caused by a single inaccuracy caused by the ground state to the motion state are avoided, and multiple sensor data are effectively integrated to improve the positioning accuracy of the self-propelled lawn mower.

[0067] An 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. A schematic diagram of the self-propelled lawn mower is shown in Figure 1. This embodiment can be applied to situations where the determination of the mowing working area of ​​the self-propelled lawn mower is optimized. The optimization of the determination of the mowing working area is performed by a controller in the self-propelled lawn mower, and the device can be implemented by software and / or hardware.

[0068] The self-propelled lawn mower includes a body and a travel wheel assembly, which is configured to support the body. The self-propelled lawn mower body refers to the hardware part used to realize the mowing function, and the travel wheel assembly refers to the component used to support the self-propelled lawn mower to move automatically.

[0069] The self-moving lawn mower also includes a wireless communication module configured to communicate with a second remote device, including receiving control signals sent by the second remote device. The second remote device is configured to control the movement of the self-moving lawn mower by sending control signals to the wireless communication module of the self-moving lawn mower. The second remote device may be a remote control device, etc. In some embodiments, the second remote device is a mobile terminal. A user can send control signals to the self-moving lawn mower through the mobile terminal to remotely control the movement of the self-moving lawn mower.

[0070] A wireless communication module is located in the self-propelled lawn mower and is configured to receive control signals transmitted by a second remote device, thereby enabling the self-propelled lawn mower to move in accordance with the control signals. In some embodiments, the wireless communication module includes at least one of the following: Bluetooth, WiFi, and cellular signals. For example, a user transmits a control signal to the wireless communication module via a mobile device. The wireless communication module receives the control signal via at least one of Bluetooth, WiFi, and cellular signals, and then controls the self-propelled lawn mower to move in accordance with the control signal.

[0071] The self-propelled lawn mower also includes a visual sensor configured to capture image data of its surroundings. The visual sensor is deployed on the self-propelled lawn mower to capture real-time image data of its surroundings while the self-propelled lawn mower is in motion. In some embodiments, the visual sensor includes a binocular camera. The self-propelled lawn mower uses the binocular camera to capture image data of its surroundings, thereby improving image data coverage.

[0072] The self-propelled lawn mower further includes a controller electrically connected to the wireless communication module and the visual sensor, respectively, to obtain the control signal and the image data. A flowchart of the process of generating the working area boundary configured by the controller is shown in FIG4 , and the specific process includes:

[0073] S21. Calculate the movement route indicated by the control signal, control the walking wheel assembly to make the self-moving lawn mower travel along the movement route, and store the coordinate information of the movement route;

[0074] S22. Identifying a boundary between grass and non-grass in the image data based on deep learning, controlling the travel wheel assembly to move the self-propelled lawn mower along the boundary, and storing coordinate information of the boundary;

[0075] S23: Integrate the coordinate information of the moving route and the coordinate information of the dividing line to generate a working area boundary of the self-propelled lawn mower.

[0076] 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 visual sensor, so as to control the movement of the self-propelled lawn mower according to the control signal and the image data.

[0077] Specifically, when a control signal is received, the moving route indicated by the control signal is calculated, the self-moving lawn mower is controlled to move along the moving route, and the coordinate information of the moving route is stored; when the control signal is missing, the boundary between grass and non-grass in the image data is identified, the self-moving lawn mower is controlled to move along the dividing line, and the coordinate information of the dividing line is stored; the coordinate information of the moving route and the coordinate information of the dividing line are integrated to generate the working area boundary of the self-moving lawn mower.

[0078] In the current related technologies, most self-propelled lawn mowers construct mowing maps by manually controlling the mower to construct a map of the mowing area. This method is 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, which determines the map boundary by identifying grass and non-grass areas, and then connects them to form an effective mowing area. For example, grass and non-grass areas are identified based on deep learning, and the grass area is the area that the self-propelled lawn mower needs to cut, so the grass area can be divided out to form a mowing map. However, for non-connected areas, it is necessary to manually send a control signal through a second remote device to remotely control the area of ​​the next piece of grass, or for complex environments, it is also possible to choose to switch to manual control composition. This embodiment ensures the safety of mowing map construction and improves the efficiency of mowing map construction.

[0079] Exemplarily, when constructing a map of the work area, the self-propelled lawn mower uses a visual sensor to capture images of the lawn and utilizes deep learning technology to identify grass and non-grass areas in the image. Deep learning is a machine learning technology that can train a neural network to recognize patterns and features in an image. The deep learning model is trained to identify grass and non-grass areas in the lawn image 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 image and outputs a classification result in which each pixel is classified as grass or non-grass, and the boundary is determined by determining the boundary between grass and non-grass pixels.

[0080] After the dividing line in the image data acquired by the current visual sensor is determined, the self-moving lawn mower is controlled to move along the dividing line. Specifically, by controlling the movement of the self-moving lawn mower, it moves along the dividing line, and records the path information traveled by the self-moving lawn mower during the movement. The path information may include the coordinates of the starting point, the end point and each point on the path of the self-moving lawn mower. The coordinate information can be determined using the built-in sensor of the self-moving lawn mower, or obtained through an external positioning system. For example, the coordinate information is obtained by the fusion positioning method in the above embodiment. In some embodiments, the self-moving lawn mower further includes a differential positioning unit configured to obtain the coordinate information. In some embodiments, the self-moving lawn mower further includes a sensor assembly configured to obtain the coordinate information. Specifically, refer to the above embodiment and no further details will be given here.

[0081] When the self-moving lawn mower moves according to the dividing line obtained during the movement, if the dividing line is closed, a virtual channel is constructed through the control signal to control the self-moving lawn mower to go to the next lawn. The self-moving lawn mower again autonomously identifies the boundary line between grass and non-grass through image data and continues to build the map. Specifically, after the self-moving lawn mower has traveled a circle along the dividing line on a lawn, the dividing line is closed. At this time, a virtual channel is constructed through a second remote device (for example, the self-moving lawn mower is remotely controlled by a remote control or APP), and the self-moving lawn mower is directed from the current lawn to the next lawn through a control signal. On the new lawn, the self-moving lawn mower can again autonomously identify the grass and non-grass areas and continue to build a map of the working area. Figure 5 shows a schematic diagram of the movement scenario of a self-propelled lawn mower constructing a work area map. In the upper half of the scene, the self-propelled lawn mower starts at point A on the left lawn and autonomously identifies the boundary line based on image data, moving in the direction indicated by the arrow. When it returns to point A, the boundary line closes. A second remote device then constructs a virtual channel from point A to point B on the right lawn. A control signal directs the self-propelled lawn mower from point A on the current lawn to point B on the next lawn, continuing to construct the work area map. In the lower half of the scene, the self-propelled lawn mower starts at point C on the lawn and autonomously identifies the boundary line based on image data, moving in the direction indicated by the arrow. When it returns to point C, the boundary line closes, confirming that there are no more lawns to be constructed, and the autonomous work area map is complete.

[0082] In some embodiments, integrating the coordinate information of the moving route and the coordinate information of the dividing line to generate the working area boundary of the self-propelled lawn mower includes:

[0083] If the coordinate information of the dividing line is located within a preset area, and the preset area includes the coordinate information of the moving route, a working area boundary of the self-propelled lawn mower within the preset area is generated according to the coordinate information of the moving route.

[0084] The preset area refers to an area with a complex environment, such as a lawn boundary with a complex environment, such as numerous trees, buildings, and other obstacles, or a lawn belonging to one's home and a neighbor's home, making it difficult to distinguish between grass and non-grass. In this case, the autonomous lawn mower may not be able to fully identify the boundary line independently. Therefore, the boundary of the working area within the preset area needs to be determined by a control signal sent by a second remote device.

[0085] For example, when encountering a complex environment, manual intervention is used to build a map of the complex environment. Once the map is built, the system switches back to the autonomous grass and non-grass recognition state. Manual intervention (e.g., remote control of the self-propelled lawn mower via a remote control or app) helps the self-propelled lawn mower build the map. Once the map of the complex environment is built, the system switches back to the autonomous recognition state.

[0086] Specifically, if the self-moving lawn mower is detected to be within a preset area, a control request message is sent to a second remote device. If a control signal from the second remote device is received, a movement route indicated by the control signal is calculated, the travel wheel assembly is controlled to move the self-moving lawn mower along the movement route, the coordinate information of the movement route is stored, and the working area boundary of the self-moving lawn mower within the preset area is generated based on the coordinate information of the movement route. If no control signal from the second remote device is received within a preset time period, a boundary between grass and non-grass in the image data is identified based on deep learning, the travel wheel assembly is controlled to move the self-moving lawn mower along the boundary, the coordinate information of the boundary is stored, and the working area boundary of the self-moving lawn mower within the preset area is generated based on the coordinate information of the boundary.

[0087] In some embodiments, the self-moving lawn mower further includes a memory configured to store coordinate information of the moving route, coordinate information of the dividing line, and the working area boundary.

[0088] After obtaining the coordinate information of the moving route, the coordinate information of the dividing line and the boundary of the working area, the information is stored in a memory to facilitate subsequent generation of a mowing map and information query.

[0089] In some embodiments, the self-propelled lawn mower transmits the work area boundary to the second remote device via the wireless communication module.

[0090] After the boundary of the working area is determined, the boundary of the working area is sent 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, the area with the problem is reconstructed.

[0091] In some embodiments, integrating the coordinate information of the movement route and the coordinate information of the boundary line includes:

[0092] The coordinate information of the movement route and the coordinate information of the boundary line are smoothed and gap-filled.

[0093] Since the coordinate information of the moving route and the coordinate information of the dividing line are obtained by the self-moving lawn mower during its movement, there will be certain discontinuities. In order to ensure the continuity and smoothness of the final generated working area boundary, the coordinate information of the moving route and the coordinate information of the dividing line are smoothed and the gaps are filled.

[0094] Once the mowing area is completely closed, a boundary map of the self-propelled lawn mower's mowing area is automatically generated based on the self-propelled lawn mower's path information. The path information includes coordinate information of the movement route and the coordinate information of the boundary line. For example, after all lawns have been closed by the self-propelled lawn mower's path, a boundary map of the self-propelled lawn mower's mowing area is automatically generated based on the path smoothing and gap filling process. The boundary map of the mowing area can display information such as the path of the self-propelled lawn mower on each lawn and the order of mowing. Based on the boundary of the work area, the self-propelled lawn mower can autonomously carry out its mowing task.

[0095] The beneficial effects of this embodiment are as follows: by visually identifying the boundary between grass and non-grass and combining the control signal of the second remote device, a mowing map of the self-propelled lawn mower is constructed, thereby improving the construction efficiency of the mowing map and the safety of the map construction.

[0096] Figure 6 is a schematic diagram of a method for building an edge for a self-propelled lawn mower according to an embodiment of the present application. This embodiment is applicable to situations where the determination of the mowing working area of ​​the self-propelled lawn mower is optimized. The method can be executed by an edge building device of the self-propelled lawn mower, which can be implemented by software and / or hardware and integrated into an electronic device. The electronic device involved in this embodiment can be a device with computing capabilities such as a server.

[0097] The self-propelled lawn mower includes a wireless communication module and a visual sensor, and the edge building method includes:

[0098] receiving a control signal sent by a second remote device through the wireless communication module;

[0099] Acquiring image data of the surrounding area of ​​the self-propelled lawn mower by the visual sensor;

[0100] calculating a movement route indicated by the control signal, controlling the self-moving lawn mower to move along the movement route, and storing coordinate information of the movement route;

[0101] When the control signal is absent, identifying a boundary line between grass and non-grass in the image data, controlling the self-propelled lawn mower to move along the boundary line, and storing coordinate information of the boundary line;

[0102] The coordinate information of the moving route and the coordinate information of the dividing line are integrated to generate a working area boundary of the self-propelled lawn mower.

[0103] In some embodiments, the second remote device is a mobile terminal.

[0104] In some embodiments, the wireless communication module includes at least one of the following: Bluetooth, WiFi, and cellular signal.

[0105] In some embodiments, the visual sensor includes a binocular camera.

[0106] In some embodiments, the self-moving lawn mower further includes a memory configured to store coordinate information of the moving route, coordinate information of the dividing line, and the working area boundary.

[0107] In some embodiments, the self-propelled lawn mower transmits the work area boundary to the second remote device via the wireless communication module.

[0108] In some embodiments, integrating the coordinate information of the movement route and the coordinate information of the boundary line includes:

[0109] The coordinate information of the movement route and the coordinate information of the boundary line are smoothed and gap-filled.

[0110] In some embodiments, integrating the coordinate information of the moving route and the coordinate information of the dividing line to generate the working area boundary of the self-propelled lawn mower includes:

[0111] If the coordinate information of the dividing line is located within a preset area, and the preset area includes the coordinate information of the moving route, a working area boundary of the self-propelled lawn mower within the preset area is generated according to the coordinate information of the moving route.

[0112] In some embodiments, the self-moving lawn mower further includes a differential positioning unit configured to obtain the coordinate information.

[0113] In some embodiments, the self-moving lawn mower further includes a sensor assembly configured to obtain the coordinate information.

[0114] The edge building method of the self-moving lawn mower provided in the embodiment of the present application can execute any embodiment method configured by the controller in the self-moving lawn mower provided in the previous embodiment of the present application, and has the ability to execute corresponding functional modules and beneficial effects.

[0115] An embodiment of the present application is another self-moving lawn mower, which can be combined with the self-moving lawn mower in the above embodiment. A schematic diagram of the self-moving lawn mower is shown in Figure 1. This embodiment can be applied to situations where the working mode of the self-moving lawn mower is optimized. The working mode includes a positioning fusion algorithm or path planning. The optimization of the working mode of the self-moving lawn mower is executed by a controller in the self-moving lawn mower, and the device can be implemented by software and / or hardware.

[0116] The self-propelled lawn mower includes a body and a travel wheel assembly, wherein the travel wheel assembly is configured to support the body. The self-propelled lawn mower body refers to the hardware part used to realize the mowing function, and the travel wheel assembly refers to the component used to support the self-propelled lawn mower to move automatically.

[0117] The self-moving lawn mower also 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-moving lawn mower. The signal receiving unit refers to a unit configured in the self-moving lawn mower for receiving the position of the self-moving lawn mower sent by an external first remote device. Specifically, the first remote device obtains the position information of the self-moving lawn mower in real time, and sends a signal to the signal receiving unit in the self-moving lawn mower based on the position information. After receiving the signal sent by the first remote device, the signal receiving unit processes the signal to obtain the position of the self-moving lawn mower. The position of the self-moving lawn mower, that is, the position information obtained by the first remote device outside the lawn mower, such as GPS positioning data, is dependent on the self-moving lawn mower.

[0118] 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 utilizes multiple satellites, ground-based receivers, and related equipment. It can determine information such as geographic location, speed, and time by receiving signals from satellites. GNSS is primarily composed of several major systems, including the Global Positioning System (GPS), Galileo, GLONASS, and the BeiDou Navigation System. These systems aim to provide high-precision navigation positioning and assisted navigation services worldwide.

[0119] Specifically, the self-propelled lawn mower is configured with a global navigation satellite system (GNSS) receiver to receive satellite signals and determine external positioning data of the self-propelled lawn mower based on the satellite signals.

[0120] In some embodiments, the signal receiving unit is a differential positioning unit, and the position of the self-moving lawn mower is a differential positioning result of the self-moving lawn mower.

[0121] The differential positioning unit is an internal device within the self-propelled lawn mower that uses differential positioning to determine external positioning data. The position of the self-propelled lawn mower obtained by applying differential positioning to the signal is the differential positioning result. Specifically, the signal receiving unit uses RTK (Real-time Kinematic) positioning to obtain RTK positioning data as the position of the self-propelled lawn mower. RTK is a measurement method that can achieve centimeter-level positioning accuracy in real time in the field.

[0122] The self-propelled lawn mower also includes a visual sensor configured to capture image data of its surroundings. The visual sensor is deployed on the self-propelled lawn mower to capture real-time image data of its surroundings while the self-propelled lawn mower is in motion. In some embodiments, the visual sensor includes a binocular camera. The self-propelled lawn mower uses the binocular camera to capture image data of its surroundings, thereby improving image data coverage.

[0123] The self-propelled lawn mower further includes a controller electrically connected to the signal receiving unit and the visual sensor, respectively. The signal quality adjustment method configured by the controller is shown in FIG7 , and the specific process includes:

[0124] S31, receiving the image data from the visual sensor;

[0125] S32. Determine the signal quality of each region in the image data using a target detection algorithm;

[0126] S33: Adjust the positioning fusion algorithm or perform path planning according to the signal quality of each area.

[0127] In some embodiments, determining the signal quality of each region in the image data by using a target detection algorithm includes:

[0128] The obstructions are detected by the target detection algorithm, and the signal quality of each area in the image data is determined according to the number, volume and / or height of the obstructions.

[0129] Because large, low obstacles can significantly impact the signals received by the signal receiving unit, signal quality must be ensured to accurately determine the position of the autonomous lawn mower using the signal received from the first remote device. Specifically, the signals received by the signal receiving unit may include satellite signals and radio signals from an RTK base station, both of which are significantly affected by obstructions.

[0130] Using visual sensors to acquire environmental image data, the image processing technology uses object detection algorithms to identify obstructing features and extract information such as their volume, height, number, and coverage area. Object detection algorithms can be implemented through image segmentation, edge detection, and feature extraction, which are common techniques used by those skilled in the art and are not detailed here.

[0131] Based on the extracted obstruction parameters, such as quantity, volume and / or height, it is determined whether the obstruction may affect the signal received by the signal receiving unit. If the obstruction is large or high, it may block the satellite signal; if the obstruction covers a large area, it may affect the propagation of the signal. Therefore, the signal quality of each area in the image data is determined based on the quantity, volume and / or height of the obstruction. Exemplarily, a mapping relationship between different intervals of the quantity, volume and / or height of the obstruction and the signal quality is pre-established, and based on the mapping relationship, the corresponding signal quality can be found according to the quantity, volume and / or height of the obstruction in each area. The specific level correspondence in the mapping relationship can be determined according to the actual scenario and is not limited here.

[0132] In some embodiments, adjusting the positioning fusion algorithm according to the signal quality of each area includes:

[0133] If the signal quality of the target area is less than a preset signal threshold, the fusion weight of the satellite positioning method in the positioning fusion algorithm is reduced.

[0134] Because 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 indicates that the signal reception result in that area may be inaccurate. Therefore, determining the position of the self-propelled lawn mower based solely on the signal will result in inaccurate position determination. If the position of the self-propelled lawn mower is determined based on a positioning fusion algorithm, in order to ensure the accuracy of the fused positioning result, it is necessary to reduce the fusion weight of the position information determined based on the signal.

[0135] Exemplarily, the method for determining the position of a self-propelled lawn mower utilizes a positioning fusion algorithm. This positioning fusion algorithm may employ the multi-sensor fusion algorithm described in the aforementioned embodiments, or may integrate a satellite positioning method with other sensor positioning methods. If the signal quality of the target area falls below a preset signal threshold, the weight of the satellite positioning method in the positioning fusion algorithm is reduced, while the weight of the other sensor positioning methods is increased. The specific reduction ratio can be determined based on the actual scenario and is not a limitation herein.

[0136] In some embodiments, the positioning fusion algorithm further includes a positioning method using at least one of vision, lidar, radar, wheel speed meter and IMU data.

[0137] Other sensor positioning methods in the positioning fusion algorithm use positioning methods based on at least one of vision, lidar, radar, wheel speed meter, and IMU data.

[0138] In some embodiments, performing path planning based on the signal quality of each area includes:

[0139] If the self-propelled lawn mower enters a target area and the signal quality of the target area is less than a preset signal threshold, the path is adjusted to control the self-propelled lawn mower to leave the target area and enter another area where the signal quality is greater than or equal to the preset signal threshold.

[0140] When a self-propelled lawn mower enters a target area where signal quality is less than a preset signal threshold, to ensure the safety of the self-propelled lawn mower, it is necessary to control the self-propelled lawn mower to quickly exit the target area and enter another area with higher signal quality, i.e., another area with signal quality greater than or equal to the preset signal threshold. In one embodiment, to ensure mowing coverage in areas with poor signal quality, a suitable path can be planned to repeatedly enter and exit areas with poor signal quality and areas with good signal quality, thereby reducing the continuous operation time in areas with poor signal quality. For example, the self-propelled lawn mower can enter the area with poor signal quality perpendicular to the long side of the area and perform a bow-shaped cutting.

[0141] For example, when the autonomous lawn mower is working at night, since the visual sensor cannot accurately identify obstructions, the autonomous lawn mower needs to avoid target areas with poor signal quality performance and adopt corresponding obstacle avoidance strategies to ensure the safety of the autonomous lawn mower.

[0142] In some embodiments, adjusting the positioning fusion algorithm or performing path planning according to the signal quality of each area includes:

[0143] generating a global signal map according to the signal quality of each area;

[0144] Adjust the positioning fusion algorithm or perform path planning based on the signal global map.

[0145] The visual sensor is combined to analyze the occlusion parameters of the obstruction, determine the signal quality of the signal received by the signal receiving unit itself, and mark the signal quality performance of the current map where the self-propelled lawn mower is traveling based on the signal quality. A global signal map carrying the signal quality of each area, namely the RTK working condition map, is obtained.

[0146] For example, while acquiring signal positioning data, the current map is marked for RTK performance, combined with the visual analysis of obstructions. This can be achieved, for example, by analyzing the RTK positioning data's errors and combining them with the visually identified obstructions' height, number, and size. If the RTK positioning data has large errors, indicating poor signal quality, the target area is marked on the map, allowing the autonomous mower to adjust its positioning fusion algorithm or perform path planning based on the global signal map.

[0147] For example, the self-propelled lawn mower adopts a corresponding obstacle avoidance strategy based on its own operating conditions and RTK performance indicators. For example, at night, since the visual sensor may not be able to accurately identify obstructions, the self-propelled lawn mower needs to avoid areas with poor RTK performance indicators. When the RTK operating conditions are poor, a positioning fusion algorithm can be performed to reduce the weight of satellite positioning results and increase the weight of other sensor positioning data to improve overall positioning accuracy and reliability. Figure 8 is a schematic diagram of a signal quality determination method for a controller configuration on a self-propelled lawn mower according to an embodiment of the present application.

[0148] In some embodiments, the self-moving lawn mower further includes a memory configured to store a signal global map variable generated according to signal qualities of the respective areas.

[0149] After generating a global signal map based on the signal quality of each area, the global signal map is stored in memory as variable data. For example, during periods of good visual information, such as daytime, the global signal map is dynamically adjusted based on real-time image data collected by the self-propelled lawn mower. During periods of poor visual information, such as nighttime, the global signal map stored in memory is used to adjust the positioning fusion algorithm or perform path planning.

[0150] This embodiment provides the following benefits: Based on both visual recognition and signal quality, the autonomous lawn mower's positioning fusion algorithm is adjusted or path planning is performed, thereby guiding the autonomous lawn mower to perform its mowing tasks safely and efficiently. This robust adjustment of the positioning fusion algorithm based on the RTK working map and path adjustment of the autonomous lawn mower improve the mowing efficiency and safety of the autonomous lawn mower.

[0151] The embodiment of the present application is another self-moving lawn mower, which can be combined with the self-moving lawn mower in the above embodiment. The schematic diagram of the self-moving lawn mower is shown in Figure 1. This embodiment can be applied to the situation where the power supply of multiple sensors of the self-moving lawn mower is optimized. The optimization of the power supply of multiple sensors is executed by the controller in the self-moving lawn mower, and the device can be implemented by software and / or hardware.

[0152] The self-propelled lawn mower includes: a body and a travel wheel assembly, wherein the travel wheel assembly is configured to support the body. The self-propelled lawn mower body refers to the hardware part for realizing the mowing function, and the travel wheel assembly refers to the component for supporting the self-propelled lawn mower to move automatically.

[0153] The self-propelled lawn mower also includes multiple sensor assemblies disposed on the body. These sensor assemblies are used to support the self-propelled lawn mower's self-propelled mowing functions, such as positioning and path planning. A power supply on the body supplies power to each of the multiple sensor assemblies as needed to enable the sensor assemblies to perform their corresponding functions.

[0154] The self-propelled lawn mower also includes a controller electrically connected to the plurality of sensor assemblies, and selectively cuts off power to the plurality of sensor assemblies. Specifically, the controller determines at least one idle sensor assembly from the plurality of sensor assemblies based on the current operating state of the self-propelled lawn mower, and cuts off power to the idle sensor assembly from the power supply device. The idle sensor assembly is one that is not currently supporting the self-propelled lawn mower's self-mowing function.

[0155] In some embodiments, the self-moving lawn mower further includes a plurality of switch elements configured to connect or disconnect the electrical connection between the plurality of sensor assemblies and the power supply device.

[0156] A switch element is provided between the power supply device and each sensor assembly. When the switch element is in the on state, the corresponding sensor assembly is electrically connected to the power supply device. When the switch element is in the off state, the corresponding sensor assembly is electrically disconnected from the power supply device. Specifically, a controller is connected to each of the switch elements and is configured to selectively disconnect power from the power supply device to at least one of the multiple sensor assemblies by controlling the multiple switch elements.

[0157] In some embodiments, the plurality of sensor components includes at least three of a differential positioning unit, a camera, a lidar, a radar, a wheel speedometer, and an IMU.

[0158] In the above embodiment, the multiple sensor components include at least three of a differential positioning unit, a camera, a lidar, a radar, a wheel speed meter and an IMU, which are used to perform multi-sensor fusion positioning of the self-propelled lawn mower, and the multiple sensor components may also include devices that support other functions.

[0159] In some embodiments, selectively cutting off the power supply provided by the power supply device to at least one of the plurality of sensor components comprises:

[0160] Whether to cut off the power supply to the differential positioning unit is selected according to the signal quality.

[0161] The differential positioning unit is configured to receive a signal sent by the first remote device to obtain external positioning data of the self-propelled lawn mower, and the signal quality refers to the quality of the signal sent by the first remote device received by the differential positioning unit.

[0162] Specifically, if the signal quality falls below a preset signal threshold, power to the differential positioning unit is cut off. For example, if the RTK signal falls below the preset signal threshold, this indicates that the RTK operating conditions in the current environment of the autonomous lawn mower are poor, and the determined external positioning data may have large errors. To improve positioning accuracy and avoid using external positioning data, power to the differential positioning unit is cut off to ensure power supply efficiency, avoid powering sensor components that contribute less to the current autonomous lawn mower, improve power conservation efficiency, and thereby increase the autonomous lawn mower's endurance.

[0163] That is, when the working conditions are not suitable for RTK positioning, the RTK and other related transmitting and receiving sensors can be turned off.

[0164] In some embodiments, after selecting whether to cut off power to the differential positioning unit based on signal quality, the method further includes:

[0165] Whether to restore power to the differential positioning unit is selected according to information from a first other sensor; wherein the first other sensor includes at least one sensor among the multiple sensors except the differential positioning unit.

[0166] 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 restored. For example, if it is currently dark, the information obtained by the camera is limited, and the power supply to the differential positioning unit is restored; or if the self-propelled lawn mower is currently traveling on a bumpy road, the information obtained by the wheel speed meter has certain errors, and the power supply to the differential positioning unit is restored. The specific restoration strategy can be determined based on the positioning fusion strategy and is not limited here. That is, when other positioning methods are inaccurate, the power supply to the differential positioning unit is restored to ensure the accuracy of the positioning result.

[0167] In some embodiments, selectively cutting off the power supply provided by the power supply device to at least one of the plurality of sensor components comprises:

[0168] Whether to cut off power supply to the camera is selected according to visually visible information.

[0169] The camera is used to detect environmental information around the self-propelled lawn mower to determine visual positioning data through the environmental information. Visually visible information refers to the number of environmental features in the image data obtained by the camera.

[0170] Specifically, if the visually visible information falls below a preset threshold, indicating a small number of features in the current environment and a certain degree of error and inaccuracy in positioning based on environmental information, power to the camera is cut off. For example, if it is currently dark, or if the current image data contains few features, indicating that the environment the self-propelled lawn mower is currently in is relatively monotonous, the determined visual positioning data may have large errors. To improve positioning accuracy and avoid using visual positioning data, power to the camera is cut off to ensure power efficiency, avoid powering sensor components that contribute less to the current self-propelled lawn mower, improve power efficiency, and thereby increase the self-propelled lawn mower's endurance.

[0171] That is, when there are few characteristic objects in the working condition, which is not conducive to visual positioning, the visual sensor can be turned off and its power supply can be stopped.

[0172] In some embodiments, after selecting whether to cut off power to the camera according to the visually visible information, the method further includes:

[0173] Whether to restore power to the camera is selected according to information from a second other sensor; wherein the second other sensor includes at least one sensor other than the camera among the multiple sensors.

[0174] If the data quality obtained by the self-propelled lawn mower's other second sensors is low, then in order to ensure the accuracy of the positioning results, the power supply to the camera is restored. For example, if the self-propelled lawn mower 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 restored. Or if the self-propelled lawn mower is currently traveling on a bumpy road, the information obtained by the wheel speed meter contains certain errors, and the power supply to the camera is restored. The specific restoration strategy can be determined based on the positioning fusion strategy and is not limited here. That is, in the event that other positioning methods are inaccurate, the power supply to the camera is restored to ensure the accuracy of the positioning results.

[0175] In some embodiments, selectively cutting off the power supply provided by the power supply device to at least one of the plurality of sensor components comprises:

[0176] At least one target sensor component is selected from the plurality of sensor components to cut off power supply according to the remaining power of the power supply device and the power of the plurality of sensor components.

[0177] If the remaining power of the power supply device is less than a first preset power threshold, and the first power threshold is greater than the preset power threshold in the next embodiment, it means that the power supply device is currently at a low power level but has not reached the recharging standard. Then, at least one high-power target sensor component is selected from the multiple sensor components according to the power of the multiple sensor components to cut off the power supply, so as to improve the subsequent endurance of the self-propelled lawn mower.

[0178] Exemplarily, if the remaining power of the power supply device is less than 50%, the multiple sensor components are sorted in descending order according to their power, and the battery life of the power supply device is calculated after the target sensor component ranked first in the sorting order is cut off in sequence, until the battery life reaches the preset standard, and the final target sensor component to be cut off is determined.

[0179] For example, when it is monitored that the self-propelled lawn mower is within a preset area within a preset time period, indicating that the self-propelled lawn mower is in a trapped state, the self-propelled lawn mower enters a low power consumption mode and stops supplying power to sensors such as the camera, differential positioning unit, and odometer.

[0180] In some embodiments, selectively cutting off the power supply provided by the power supply device to at least one of the plurality of sensor components comprises:

[0181] If the remaining power of the power supply device is less than a 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 power supply to non-path planning associated sensor components is cut off.

[0182] If the remaining power of the power supply device is low and recharging is required, in order to ensure smooth recharging, the power supply to the non-path planning related sensor components is cut off, and only the sensor components related to path planning required during recharging are powered.

[0183] For example, when the self-propelled lawn mower cannot continue to work due to low battery and needs to be recharged, the power supply to the unreliable sensor components can be cut off according to the characteristics of the planned path to ensure that the remaining power can support the self-propelled lawn mower to return to the charging station.

[0184] In some embodiments, selectively cutting off the power supply provided by the power supply device to at least one of the plurality of sensor components comprises:

[0185] Choose whether to cut off the power supply to the IMU based on road bump information.

[0186] Among them, road bump information refers to the status information of the road surface on which the self-propelled lawn mower is currently traveling. It can be determined by image data obtained by a visual sensor deployed on the body of the self-propelled lawn mower, or by vibration data obtained by a vibration sensor deployed on the body of the self-propelled lawn mower. It can also be determined in other ways and is not limited here.

[0187] If it is determined based on the road bump information that the bumpiness of the road on which the self-propelled lawn mower is currently traveling exceeds a threshold, and since the accuracy of the IMU decreases on bumpy roads, resulting in reduced reliability of data obtained by the IMU, power supply to the IMU is cut off.

[0188] The beneficial effects of this embodiment are as follows: by monitoring the different working conditions 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 mowing task more efficiently and for a longer period of time, thereby achieving the power-saving and endurance function of the self-propelled lawn mower. The above shows and describes the basic principles, main features and advantages of this application. Those skilled in the art should understand that the above embodiments do not limit this application in any form, and any technical solutions obtained by equivalent replacement or equivalent transformation fall within the scope of protection of this application.

Claims

1. 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 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, electrically connected to the signal receiving unit, the first sensor assembly, and the second sensor assembly, and the fusion positioning unit is configured to: Locate the self - propelled lawn mower according to the environmental information, and fuse the external positioning data to generate a first positioning result; Locate the self - propelled lawn mower according to the motion state, and fuse the external positioning data to generate a second positioning result; 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, wherein, The signal receiving unit is a Global Navigation Satellite System (GNSS) receiver.

3. The self-propelled lawn mower according to claim 2, wherein, 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, wherein, The first sensor assembly includes a camera assembly.

5. The self-propelled lawn mower according to claim 1, wherein, Locating the self - propelled lawn mower according to the environmental information includes: Locating the self - propelled lawn mower based on Visual Simultaneous Localization and Mapping (VSLAM) according to the environmental information.

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

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

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

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

10. The self-propelled lawn mower according to claim 1, wherein, Fusing the first positioning result and the second positioning result to generate a final positioning result, includes: Adjusting 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; Fusing the first positioning result and the second positioning result according to the fusion weights to generate a final positioning result.

11. 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 visual sensor configured to acquire image data around the self - propelled lawn mower; A controller, electrically connected to the wireless communication module and the visual sensor respectively, to acquire the control signal and the image data; Wherein, 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 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, wherein, The second remote device is a mobile terminal.

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

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

15. The self-propelled lawn mower according to claim 11, further comprising a memory configured to store 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, wherein, 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: Performing 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 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, further comprising a differential positioning unit configured to obtain the coordinate information.

20. A method for building 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 building a boundary including: 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; Calculating the moving route indicated by the control signal, controlling the self-propelled lawn mower to travel along the moving route, and storing 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, comprising: 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, the signal being used to determine the position of the self-propelled lawn mower; A vision sensor configured to obtain image data around the self-propelled lawn mower; A controller electrically connected to the signal receiving unit and the vision sensor respectively; Wherein, 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 mower is the differential positioning result of the self-propelled mower.

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

25. The self-propelled lawn mower according to claim 21, wherein, By using an object detection algorithm, determine the signal quality of each region in the image data, including: Detect obstacles through the object detection algorithm, and determine 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, wherein, Adjust the positioning fusion algorithm according to the signal quality of each region, including: If the signal quality of the target region is less than a preset signal threshold, reduce the fusion weight of the satellite positioning method in the positioning fusion algorithm.

27. The self-propelled lawn mower according to claim 26, wherein, 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, Perform path planning according to the signal quality of each region, including: If the self-propelled mower enters a target region and the signal quality of the target region is less than a preset signal threshold, adjust the path to control the self-propelled 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, Adjust the positioning fusion algorithm or perform path planning according to the signal quality of each region, including: Generate a signal global map according to the signal quality of each region; Adjust the positioning fusion algorithm or perform path planning according to the signal global map.

30. The self-propelled mower according to claim 29, further comprising a memory configured to store a signal global map variable generated according to the signal quality of each region.

31. A self-propelled mower, comprising: A fuselage; A traveling wheel assembly configured to support the fuselage; A plurality of sensor components disposed on the fuselage; A controller electrically connected to the plurality of sensor components respectively; A power supply device disposed on the fuselage and configured to supply power to the controller and the plurality of sensor components; Wherein, 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.

32. The self-propelled mower according to claim 31, further comprising a plurality of switch elements configured to connect or disconnect the electrical connection between the plurality of sensor components and the power supply device.

33. The self-propelled lawn mower according to claim 31, wherein, The plurality of sensor components 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, wherein, Selectively cutting off the power supply of the power supply device to at least one of the plurality of sensor components includes: Select whether to cut off the power supply to the differential positioning unit according to the signal quality.

35. After the method of the self-propelled mower according to claim 34 selects whether to cut off the power supply to the differential positioning unit according to the signal quality, the method further includes: Select whether to resume the power supply to the differential positioning unit according to the information of a 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, wherein, Selectively cutting off the power supply of the power supply device to at least one of the plurality of sensor components includes: Select whether to cut off the power supply to the camera according to the visually visible information.

37. The self-propelled lawn mower according to claim 36, after selecting whether to cut off the power supply to the camera according to the visually visible information, the method further includes: Select whether to restore the 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 plurality of sensors.

38. 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 plurality of sensor components includes: Selecting at least one target sensor component from the plurality of sensor components to cut off the power supply according to the remaining power of the power supply device and the power of the plurality of 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 plurality of 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 plurality of 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, wherein, Selectively cutting off the power supply of the power supply device to at least one of the plurality of sensor components includes: Select whether to cut off the power supply to the IMU according to the road surface bump information.

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