A path planning method, a self-moving device and a storage medium

Abstract

The present disclosure provides a path planning method, a self-moving device and a storage medium. The method comprises determining a missing area formed by the self-moving device deviating from a preset work path and / or a working component not covering. At least two missing areas are merged into a combined area according to spatial distribution characteristics. A compensation path covering the combined area is planned, and the compensation path is configured to guide the self-moving device to move continuously in the combined area, and the working component performs lawn care tasks during the movement. Thus, based on the path planning method provided by the present disclosure, the self-moving device can timely identify the missing area and perform the lawn care task to improve the completion of the work. In addition, the compensation path can be constructed based on the clustering result of the missing area, so that each individual missing area can be processed simultaneously in one compensation path, which reduces the work time compared to performing lawn care tasks for each missing area individually, thereby improving the overall work efficiency.

Description

Path planning method, self-mobile device and storage medium Technical Field

[0001] The present disclosure relates to the technical field of path planning, and in particular to a path planning method, a self-mobile device, and a storage medium. Background Art

[0002] Autonomous devices can be devices with autonomous mobility capabilities that can move autonomously and perform lawn care tasks without human intervention. For example, autonomous devices include drones, robot vacuums, and robot lawn mowers.

[0003] When performing lawn care tasks on a mobile device, the user aims to achieve complete coverage of the lawn care area through movement. However, due to the influence of the actual execution environment, some areas may be missed, thus affecting the execution of the lawn care task. Therefore, how to eliminate missed areas is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0004] In view of this, an embodiment of the present disclosure provides a path planning method, which is applied to a self-moving device having a working component, wherein the self-moving device is configured to move along a preset working path and perform a lawn care task via the working component during movement. The method includes:

[0005] Determining a missed area, wherein the missed area is formed by the self-moving device deviating from the preset working path and / or the working component not covering it;

[0006] merging at least two of the missing areas into a combined area according to spatial distribution characteristics;

[0007] A compensation path covering the combined area is planned, wherein the compensation path is configured to guide the self-moving device to continuously move in the combined area, and the working component performs the lawn care task during the movement.

[0008] In some embodiments, merging at least two of the missing regions into a combined region according to the spatial distribution characteristics includes:

[0009] Determining spatial distribution characteristics between the missing areas, wherein the spatial distribution characteristics include spatial distance, spatial density, and spatial direction;

[0010] Selecting at least two of the missing areas whose spatial distribution characteristics meet a preset spatial distribution condition;

[0011] At least two of the missing regions are merged into one combined region, wherein the combined region covers each of the missing regions.

[0012] In some embodiments, the spatial distribution conditions include:

[0013] The spatial distance between the two missed areas is less than a preset distance threshold.

[0014] In some embodiments, merging at least two of the missing regions into one combined region comprises:

[0015] determining a boundary of each of the at least two missing regions;

[0016] Boundary fitting is performed on the boundaries of each missing region to obtain the combined region.

[0017] In some embodiments, performing boundary fitting on the boundaries of each missing region to obtain the combined region includes:

[0018] Draw a circumscribed rectangle for each missing area boundary along different directions;

[0019] Determine the smallest circumscribed rectangle among the circumscribed rectangles according to geometric features, wherein the geometric features include area, side length, and aspect ratio;

[0020] The area covered by the minimum circumscribed rectangle is used as the combined area.

[0021] In some embodiments, selecting the minimum bounding rectangle corresponding to each missing area according to the geometric attributes includes:

[0022] The smallest circumscribed rectangle among all circumscribed rectangles is used as the minimum circumscribed rectangle; or

[0023] The circumscribed rectangle with the smallest side length among all circumscribed rectangles is used as the minimum circumscribed rectangle; or

[0024] The circumscribed rectangle with the largest aspect ratio among the circumscribed rectangles is used as the minimum circumscribed rectangle.

[0025] In some embodiments, the compensation path includes a plurality of straight paths and a plurality of turning paths, and adjacent straight paths are connected by turning paths.

[0026] In some embodiments, planning a compensation path covering the combined area includes:

[0027] Determine the long side and the short side of the minimum circumscribed rectangle, wherein the length of the long side is greater than the length of the short side;

[0028] The straight path is determined according to the long side.

[0029] In some embodiments, determining the straight path according to the long side includes:

[0030] determining the direction of the long side;

[0031] The direction of the straight path is determined according to the direction of the long side.

[0032] In some embodiments, planning a compensation path covering the combined area includes:

[0033] Determining a preset operation path covered by the minimum circumscribed rectangle;

[0034] The straight portion of the preset operation path within the minimum circumscribed rectangle is used as the straight path.

[0035] In some embodiments, planning a compensation path covering the combined area includes:

[0036] determining a straight direction of the straight portion of the preset operation path;

[0037] The direction of the straight path of the compensation path is determined according to the straight direction of the straight portion of the preset working path.

[0038] In some embodiments, the preset operation path guides the self-moving device to move within the lawn care area;

[0039] The further step includes: determining a position of the circumscribed rectangle in the lawn care area;

[0040] A type of the turning path is determined based on the position.

[0041] In some embodiments, it further includes:

[0042] selecting at least two spatial distribution characteristics of the missing area;

[0043] Merging at least two of the missing regions according to at least two spatial distribution conditions to obtain at least two combined regions;

[0044] Planning compensation paths covering each combined area, and calculating compensation time corresponding to each compensation path;

[0045] The combined area is selected according to the compensation time.

[0046] In some embodiments, selecting the combined area according to the compensation time includes:

[0047] The compensation times are sorted, and the combination area is selected according to the sorting result.

[0048] In some embodiments, further comprising:

[0049] Determining whether a blocking condition is satisfied between at least two of the missing areas;

[0050] When the blocking condition is met, at least two of the missing areas are divided into different combined areas.

[0051] In some embodiments, the blocking conditions include one or more of the following conditions:

[0052] The height difference between the omitted areas is greater than a preset height threshold;

[0053] There are impassable obstacles between the omitted areas;

[0054] The cutting parameters between the omitted regions are different.

[0055] In some embodiments, it further includes:

[0056] determining the area of ​​the missing region;

[0057] Ignore missed regions whose area is smaller than the area threshold.

[0058] In a second aspect, the present disclosure provides a self-propelled device, comprising:

[0059] a work component configured to perform lawn care tasks;

[0060] a moving component configured to drive the working component to move so that the working component performs the lawn care task while moving; and

[0061] A processor is configured to connect with the moving component and the working component to implement any one of the methods described.

[0062] In some embodiments, the working assembly includes a cutting assembly;

[0063] The processor is configured to plan an operating path for the self-moving device in the lawn care area based on a map of the lawn care area, and output a first instruction to the cutting component and the moving component to control the self-moving device to autonomously traverse the lawn care area along the operating path and mow the lawn in one step, wherein the mowing in one step is achieved by synchronously chopping or collecting grass during mowing.

[0064] In a third aspect, the present disclosure provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to perform any one of the methods described above.

[0065] Embodiments of the present disclosure provide a path planning method, a self-mobile device, and a storage medium. Based on the path planning method provided herein, the self-mobile device can promptly identify missed areas and execute lawn care tasks, thereby improving job completion. Furthermore, a compensation path can be constructed based on the clustering results of missed areas, allowing each individual missed area to be processed simultaneously within a single lawn care task. This reduces operation time compared to executing lawn care tasks for each missed area individually, thereby improving overall operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0067] FIG1 is a diagram of an application scenario of a mobile device provided by an exemplary embodiment of the present disclosure.

[0068] FIG2 is a schematic structural diagram of a self-moving device provided by an exemplary embodiment of the present disclosure.

[0069] FIG3 is a flow chart of a path planning method provided by an exemplary embodiment of the present disclosure.

[0070] FIG4 is a schematic diagram of a flow chart of executing a preset algorithm provided by an exemplary embodiment of the present disclosure.

[0071] FIG5 is a schematic diagram of determining a set of missing regions provided by an exemplary embodiment of the present disclosure.

[0072] FIG6 is a schematic diagram of a grid map provided by an exemplary embodiment of the present disclosure;

[0073] FIG7 is a schematic diagram of a compensation operation path provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0074] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following will provide a clear and complete description of the technical solutions in the embodiments of the present disclosure, in conjunction with the accompanying drawings. It should be understood that the described embodiments represent only a portion of the embodiments of the present disclosure, and are not intended to be exhaustive. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present disclosure without inventive effort are intended to fall within the scope of protection of the present disclosure. A self-propelled device is suitable for performing at least one lawn care task in a lawn care area and generally includes a body, a mobile component connected to the body, a sensor component, a working component, and a control circuit. The control circuit is coupled to the mobile component, the sensor component, and the working component, and controls the movement of the mobile component and the working component based on sensor data output by the sensor component. The sensor component may include, but is not limited to, at least one of a vision component, a positioning device, a collision sensor component, and an ultrasonic sensor component. The mobile component generally includes a drive motor and a drive wheel connected to the drive motor. Optionally, it may also include a driven wheel that, together with the drive wheel, drives the self-propelled device. The working component may include, but is not limited to, at least one of a bladed disc for mowing grass, a blower head for blowing away fallen leaves, and a snowplow head for sweeping snow.

[0075] In some embodiments, the work components may be determined based on the type of lawn care required to be performed by the mobile device 110. For example, for a cleaning task, the work components may include a leaf blower head or a snow blower head. For another example, for a cutting task, the work components may include a cutter head. For another example, for a spraying task, the work components may include a spraying component.

[0076] In some embodiments, the mobile component can be selected based on the actual operating environment of the autonomous device 110. For example, for an autonomous device that moves on the ground, the mobile component can be a device that enables movement on the road, such as tires or tracks. For another example, for an autonomous device that moves in the air, the mobile component can be a device that enables movement in the air, such as an air propeller or a jet engine.

[0077] Lawn care tasks for autonomous devices are generally mobile tasks, meaning they must operate while on the move. For example, a drone's lawn care task might involve flying within a target area and spraying pesticides or water. Another example is a robotic lawn mower, which can mow the lawn while moving, release insecticides or fragrances while moving, or even blow away fallen leaves or collect scattered grass.

[0078] Taking lawn mowing robots as an example, the above-mentioned lawn mowing robots that can work autonomously are currently mainly used in the home field, and lawn mowing robots using intelligent control are rarely seen in the commercial lawn mowing field.

[0079] In the commercial lawn mowing sector, commercial teams typically drive transport vehicles loaded with robotic lawn mowers and other garden tools to different user homes throughout the day, following pre-ordered tasks. These tasks include mowing, edging, pruning, leaf blowing, and other tasks. These tasks are typically completed manually, resulting in high labor costs for the team. Furthermore, factors such as weather, terrain, and the distribution and growth of vegetation all affect the team's operating time. The longer the operating time, the greater the commercial team's labor costs. Furthermore, for commercial robotic lawn mowers, the driving skills of different individuals within the commercial team vary, which can lead to inconsistencies in work efficiency and cutting quality.

[0080] In some special cases, some commercial teams have replaced commercial robotic lawn mowers with multiple small household robotic lawn mowers to reduce manpower and achieve automated mowing. However, this approach typically requires multiple intelligent lawn mowers, which is still costly. Furthermore, household robotic lawn mowers are typically slow and inefficient, making them suitable for daily maintenance tasks involving stable grass conditions. Commercial robotic lawn mowers, on the other hand, are typically used on lawns with varying grass conditions (such as tall and / or dense grass in poor conditions), and each mowing cycle must meet a certain quality requirement, requiring no further maintenance within a certain period (e.g., one to two weeks). In other words, household robotic lawn mowers typically operate once a day, while commercial robotic lawn mowers typically operate once every one to two weeks. During lawn maintenance, to ensure full coverage of the lawn care area, a full-coverage path planning algorithm can be used to pre-plan the robot's path within the lawn care area. However, in practice, due to the terrain of the lawn care area, commercial robotic lawn mowers can easily miss areas during operation. For example, a commercial lawn mower robot moving across a lawn may miss areas if the lawn care area includes slopes, ditches, or irregular edges. Another example is that when executing a pre-set path, the robot's motion may be unstable due to environmental factors (such as wind, terrain, and obstacles), resulting in missed areas.

[0081] For ease of explanation, the lawn care area can be divided into missed areas and non-missed areas. Missed areas are formed when the mowing robot deviates from the preset working path and / or is not covered by the working components. Conversely, non-missed areas are formed when the mowing robot follows the preset working path and is covered by the working components. In layman's terms, if the mowing robot moves along the preset working path, there will be no areas of the lawn care area that are not cut by the working components. However, if the mowing robot occasionally deviates and its actual path deviates from the preset working path, a missed area will be created between the actual path and the preset working path, i.e., the lawn in the missed area is not cut by the working components.

[0082] These missed areas directly impact the completion of mobile lawn care tasks. Missing areas indicate that portions of the lawn remain uncut, and the height of the lawn in these missed areas appears higher than in the remaining areas, affecting the overall lawn appearance. Specifically, because household lawn mowers are small and cut a small amount per session, they typically operate daily. The height difference between missed and remaining areas is minimal, making it unnoticeable to the user and not affecting the user's perception.

[0083] However, hiring a commercial team to maintain the lawn every day is very expensive, so most users will choose to pair a commercial team with a commercial lawn mower robot. Compared to a household lawn mower robot, a commercial lawn mower robot can increase the amount of grass cut per time to reduce the number of times a commercial team is hired, specifically once every 1-2 weeks. In certain seasons with abundant rainfall, strong sunlight, and suitable temperatures, grass grows faster. Therefore, when there are missed areas, the height difference between the missed areas and the non-missed areas of the commercial lawn mower robot is large, sometimes even reaching more than five centimeters. The user can feel it strongly with the naked eye. If the missed areas are not mowed, it will affect the user's favorability towards the commercial team. Therefore, it is more important for commercial lawn mower robots to mow the missed areas.

[0084] In embodiments of the related art, there are generally two modes for compensating for missed areas. One is real-time compensation, where operations are immediately stopped and compensation is performed when a missed area is created; the other is completion compensation, where missed areas are compensated one by one after the lawn care task is completed. In some embodiments, when the self-moving device is a robotic lawn mower, mowing missed areas can be considered a form of compensation. Of course, when the self-moving device is an automatic irrigation machine, watering missed areas can be considered a form of compensation. When the self-moving device is an automatic leaf blower, blowing away fallen leaves can be considered a form of compensation.

[0085] This disclosure first briefly describes how commercial robotic lawn mowers perform lawn care tasks and how to perform follow-up mowing:

[0086] After the business team transports or controls the commercial mower to the lawn care area, the commercial mower robot can first obtain a map drawn by the business team and use the map to determine a preset operating path. The operating path can be pre-designed by the business team, generated by the commercial mower robot on the fly, or specified by the owner of the lawn care area. This disclosure is not limited to this. After obtaining the preset operating path, the commercial mower robot will strictly follow the preset operating path to perform the lawn care task. As the commercial mower robot performs the lawn care task along the preset operating path, the lawn will be cut. Generally, when the commercial mower robot's movement center strictly follows the preset operating path to perform the lawn care task, no missed areas will be generated. However, the outdoor environment in which the lawn is located is very complex and can easily affect the commercial mower robot, causing its movement center to not strictly follow the preset operating path to perform the lawn care task. In this case, missed areas may occur. In some embodiments, the movement center can be the geometric center of the commercial mower robot or the center of its positioning module. At this time, the commercial lawn mower robot will solve the missed areas, but the current method is usually to solve the missed areas as soon as they appear. It is easy for the commercial lawn mower robot to turn around and retreat repeatedly, so the efficiency is low.

[0087] Therefore, commercial lawn mower robots face at least the following technical challenges in real-time compensation for missed areas: Compensation is typically performed by planning paths based on the center of each missed area, thus compensating each missed area individually. Even for relatively close missed areas, individual compensation is required, significantly slowing down the compensation process.

[0088] Based on the above technical problems, the present disclosure provides a path planning method, a self-mobile device and a storage medium. The path planning method provided by the present disclosure can determine the missing areas in the lawn care area, and cluster the missing areas so that at least two missing areas are processed into a combined area, determine the compensation path of the combined area, and guide the self-mobile device to simultaneously perform lawn care tasks (compensation) for at least two missing areas in the combined area through the compensation path. In the present disclosure, the processing means include aggregation, merging or selection, etc. Therefore, based on the path planning method provided by the present disclosure, the self-mobile device can simultaneously identify at least two missing areas and perform lawn care tasks for at least two missing areas in a continuous compensation path to improve the operation coverage of the self-mobile device for the lawn care area. In addition, the compensation path can be constructed based on the clustering results of the missing areas, so that at least two missing areas can be processed simultaneously in one lawn care task. Compared with performing lawn care tasks on each missing area separately and sequentially, the operation time is reduced to improve the overall operation efficiency.

[0089] As shown in Figure 1 , the control method in the disclosed embodiments is applied to a self-propelled device 110, which is configured to travel and / or operate within a lawn care area 200. The self-propelled device 110 and the lawn care area 200 can be adaptively adjusted based on actual needs. For ease of description, this disclosure uses a lawn mowing robot as an example. Those skilled in the art can adapt the technical content to accommodate self-propelled devices such as drones, robot vacuums, seeding robots, irrigation robots, leaf blowers, and insect repellent robots.

[0090] In some embodiments, the self-mobile device 110 may be a robotic lawn mower for performing mowing operations, and the lawn care area 200 may be a lawn to be mowed. The self-mobile device 110 may move and mow the lawn in the lawn care area 200 according to a set lawn care task. During the mowing process of the self-mobile device 110, missed areas (unmowed areas) may appear in the lawn care area 200. Based on the path planning method provided in the present disclosure, the self-mobile device 110 can generate a compensation path based on a clustering algorithm, thereby performing the lawn care task (mowing) in the missed areas.

[0091] In one embodiment of the present disclosure, a user can interact with a mobile device 110 through a user terminal 120. As shown in FIG1 , the mobile device 110 can obtain lawn care tasks sent by the user terminal 120 through the network 130, and can also send the completion status of the lawn care tasks to the user terminal 120 through the network 130. Lawn care tasks include, but are not limited to, job types and lawn care areas 200. The user terminal 120 is a terminal device that can establish a communication connection with the mobile device 110 to send control instructions, and the control instructions may include mobile lawn care tasks. As shown in FIG1 , the user terminal 120 can be one of a mobile device 120-1, a tablet computer 120-2, a laptop computer 120-3, a desktop computer 120-4, or any combination thereof, having input and / or output functions.

[0092] In some embodiments, it is considered that the preset operation path planning process may involve multi-party interaction. For example, the aforementioned self-moving device 110 may include multiple devices, and cooperate with each other to complete the lawn care task. For another example, the user terminal 120 may also be related to the path planning process (such as setting the operation boundary). Then the aforementioned controller 210 can also be configured as a collection of computing devices involved in the path planning process. For example, the controller 210 may include relevant devices for setting the path planning area at the user terminal 120 and relevant controllers of each self-moving device 110.

[0093] In another embodiment of the present disclosure, a map of the lawn care area 200 may be pre-downloaded to the storage medium 220 or the controller 210 of the mobile device 100, and the mobile device 110 performs mobile operations in the lawn care area 200 based on the map of the lawn care area 200 and the set mobile lawn care tasks.

[0094] Among them, the controller 210 can be a computing device that executes the path planning method provided by the present disclosure. For example, the path planning method provided by the present disclosure is executed by the self-mobile device 110, and the controller 210 may include a controller (such as an embedded controller) that is set in the self-mobile device 110 and integrated with a path planning algorithm. For another example, the path planning method provided by the present disclosure is executed by a cloud server, and the controller 210 may include a computing device (such as a CPU, SOC, etc.) in the cloud server. At this time, the cloud server can configure the processing results of the path planning method provided by the present disclosure as control instructions for each controller in the self-mobile device 110, and send it to the self-mobile device 110 via the network 130, so that the self-mobile device 110 responds to the control instructions of the cloud processor.

[0095] In the present disclosure, the network 130 can be any one or more of a wired network or a wireless network. For example, the network 130 may include a cable network, a fiber optic network, a telecommunications network, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network (ZigBee), a near field communication (NFC), an intra-device bus, an intra-device line, a cable connection, etc., or any combination thereof. The network connection between each part may be in one of the above-mentioned ways, or in multiple ways. In some embodiments, the network may be a point-to-point, shared, centralized, or other topological structure or a combination of multiple topological structures. In some embodiments, the network 130 may include one or more network access points. One or more components within the application scenario may be connected to the network 130 to exchange data and / or information.

[0096] Exemplary self-moving equipment

[0097] To further illustrate the process of the mobile device 100 executing the path planning method, the internal structure of the mobile device will be further described below with reference to FIG. 2 .

[0098] As shown in FIG. 2 , the self-mobile device 110 may include but is not limited to a working component 111 , a moving component 112 , a sensor component 113 , and a controller 210 .

[0099] The specific composition of the working assembly 111, the mobile assembly 112, and the sensor assembly 113 can be tailored to the functionality of the self-mobile device 110 and adjusted based on actual operational requirements. For example, in a lawn mower robot, the working assembly 111 may include a blade for mowing. The mobile assembly 112 typically includes a drive motor and a motion device (such as tires or tracks) connected to the drive motor. The sensor assembly 113 may include at least one of a visual sensor, a positioning device, a collision sensor, and an ultrasonic sensor.

[0100] The aforementioned working component 111, moving component 112 and sensor component 113 can change the working state in response to the control instruction. Among them, the control method of the working component 111, moving component 112 and sensor component 113 can be adjusted according to the actual situation. For example, the working component 111 and the moving component 112 can be driven by a motor. When controlling the working component 111 and the moving component 112, it is necessary to generate a corresponding motor drive signal (generally including a motor power supply signal and a Hall signal). For another example, the working component 111, the moving component 112 and the sensor component 113 are driven by a corresponding controller (such as a domain controller, a domain controller, a microcontroller, etc.). Then, the corresponding controller can achieve control by generating a corresponding control signal.

[0101] In some embodiments, the controller 210 may include one or more sub-processing devices (e.g., a single-core processing device or a multi-core multi-core processing device). By way of example only, the controller 210 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, or any combination thereof.

[0102] In the present disclosure, the mobile device 110 may further include a storage medium 220 integrated into the mobile device. The storage medium 220 may store instructions / data within the mobile device 110. Specifically, the storage medium 220 may store instructions related to the path planning method of the present disclosure, so that after the relevant instructions are called by the controller 210, the path planning method provided by the embodiment of the present disclosure is implemented. In addition, the storage medium 220 may also cache relevant data (such as grid maps, sensor data, etc.) during the execution of the path planning method to ensure the execution of the path planning method.

[0103] In one embodiment of the present disclosure, the controller 210 may be integrated into the mobile device 110. For example, the mobile device 110 may be provided with a computing device such as a printed circuit board (PCB), a system on chip (SOC), or an electronic control unit (ECU). The processing unit (such as a CPU) in the computing device may serve as the controller 210, and the storage unit (such as a RAM and a ROM) may serve as the storage medium 220.

[0104] In the present disclosure, the controller 210 can provide control signals to the working component 111, the moving component 112, and the sensor component 113 to control their operating states. In one embodiment of the present disclosure, when the working component 111, the moving component 112, and the sensor component 113 are directly driven by motors, the controller 210 can generate motor drive signals based on a preset protocol to control at least one of the working component 111, the moving component 112, and the sensor component 113.

[0105] In one embodiment of the present disclosure, the controller 210 may include a path planning device 230, which provides control signals to the working component 111, the moving component 112, and the sensor component 113 to control their operating states. As shown in FIG2 , the path planning device 230 may include a non-missing area determination component unit 231, a missing area determination component unit 232, a combined area determination component unit 233, and a path planning component unit.

[0106] The non-missing area determination component unit 231 may be used to control the mobile device to perform a lawn care task on the target lawn care area along a preset operation path, and determine the non-missing area in the target lawn care area.

[0107] The missing area determination component 232 may be used to determine missing areas in a lawn care area.

[0108] The combined region determining component unit 233 may be configured to merge at least two missing regions into one combined region according to a preset algorithm.

[0109] The path planning component unit 234 can be used to plan a compensation path for the self-moving device and perform the lawn care task on the combined area based on the compensation path.

[0110] In the present disclosure, the path planning device 230 determines a preset operating path for the self-moving device and generates corresponding control signals in real time based on the preset operating path. The signals are sent to the working component 111 and the mobile component 112, so that the self-moving device, driven by the mobile component 112, moves along the preset operating path and performs mobile operations through the working component 111. The controller 210 can determine the non-missing areas and the missing areas based on the execution of the preset operating path by the working component 111 and the mobile component 112.

[0111] The functions of the aforementioned missing area determination component unit 232 can be implemented by the sensor component 113, the controller 210, and the storage medium 220. That is, the sensor component 113 can sense the position of the self-mobile device 110 in real time and store it in the storage medium 220. The controller 210 can determine the missing area based on the real-time position of the self-mobile device 110 (for example, based on a grid map).

[0112] The functions of the aforementioned combined region determination component unit 233 may be implemented by the controller 210 and the storage medium 220. That is, the controller 210 may perform processing (such as clustering) based on the missing regions in the storage medium 220 to determine a combined region containing multiple missing regions.

[0113] The functions of the aforementioned path planning component unit 234 can be implemented by the working component 111, the moving component 112, and the controller 210. Specifically, the controller 210 can determine a compensation path based on the combined area, generate corresponding control signals based on the compensation path, and transmit them to the working component 111 and the moving component 112 to cause the self-moving device to move along the compensation path and perform a mobile operation, thereby completing the lawn care task for the missed area.

[0114] It should be noted that the division of functional units in the embodiments of the present disclosure can be adjusted based on actual needs. That is, the division of functional units in the embodiments of the present disclosure is illustrative and merely represents a logical functional division. In actual implementation, other division methods may be used. For example, two or more functional units may be integrated into a single unit. Furthermore, the aforementioned integrated functional units may be implemented in either hardware or software functional modules.

[0115] The following describes in detail the path planning method based on missed areas provided by the present disclosure based on the aforementioned application scenarios and mobile devices.

[0116] Exemplary Path Planning Method

[0117] Most existing path planning methods are based on fixed grid division or real-time perception of missed areas for path filling, but they do not fully consider the spatial distribution characteristics of missed areas. They often adopt a one-by-one compensation approach, which leads to problems such as repeated U-turns of self-moving equipment, path overlap, extended operation time, and affected overall efficiency.

[0118] As shown in FIG3 , in some embodiments, the controller 210 can independently control or control the mobile device 110 through the path planning device 230 to perform the following steps:

[0119] S310 : Determine a missed area, where the missed area is formed by the self-moving device deviating from the preset working path and / or the working component not covering the missed area. In some embodiments, S310 may be executed by the controller 210 or the missed area determination unit 232 .

[0120] S320: Merge at least two of the missing regions into a combined region according to the spatial distribution characteristics. In some embodiments, S320 may be executed by the controller 210 or the combined region determination component unit 233.

[0121] S330: Plan a compensation path covering the combined area, wherein the compensation path is configured to guide the self-moving device to continuously move within the combined area, and the working component performs the lawn care task during the movement. In some embodiments, S330 can be performed by the controller 210 or the path planning unit 234.

[0122] A lawn care task may refer to a task that a mobile device is configured to perform. In some embodiments, a lawn care task can be set by a user via a user terminal. For example, a user may input a lawn care area and task requirements into the mobile device via the user terminal to determine the lawn care task to be performed by the mobile device. For example, for a robotic lawn mower, a lawn care task may include mowing within a lawn care area. The lawn care area refers to the area to be mowed, and the task requirements may refer to the remaining height of the lawn after mowing.

[0123] It should be noted in particular that the compensation path is configured to guide the self-moving device to move continuously in the combined area. The "continuous" here can mean that the self-moving device performs a single movement along the compensation path. During the movement, the area covered by the working component will not be covered again by the working component, thereby avoiding path overlap and repeated U-turns.

[0124] A lawn care area may refer to an area that a mobile device needs to cover to perform a lawn care task.

[0125] The preset operation path can be a path of the self-propelled device based on the lawn care area. When the self-propelled device moves along the starting position of the preset operation path to the end position of the preset operation path, the self-propelled device can theoretically complete the lawn care task in the lawn care area.

[0126] In some embodiments, a self-moving device needs to complete lawn care tasks in a target lawn care area based on a preset operating path. The preset operating path can be a full-coverage path based on the single operating width of the working component. That is, the plane formed by expanding the preset operating path based on the single operating width can completely cover the lawn care area. As just one example, the present disclosure can employ a bow-shaped full-coverage path planning algorithm for full-coverage path planning to determine the preset operating path. In the present disclosure, when the self-moving device is a lawn mowing robot, the working component can be a cutting component, and the area covered by the working component refers to the area formed after the cutting component performs cutting.

[0127] In some embodiments, the aforementioned S310 can be performed based on the execution of the preset operation path by the mobile device. That is, the execution of the preset operation path by the mobile device can be determined by recording the movement path of the mobile device, thereby using the portion of the target lawn care area corresponding to the completed preset operation path in the lawn care area currently located by the mobile device as the completed lawn care area.

[0128] In the present disclosure, a missed area may refer to an area within a lawn care area where a mowing robot deviates from a preset operating path and is cut as a result of the robot's deviation from the preset operating path. For example, a missed area may include areas cut by a self-propelled device due to interference from the actual operating environment (such as obstacles, slopes, etc.). For example, a preset operating path passes through a slope, and the preset operating path is located in the middle of the slope. Due to the steep slope, if the mowing robot's lateral anti-skid function cannot ensure stable movement along the preset operating path, the mowing robot will slide from the top of the slope to the bottom. At this time, the mowing robot's actual path and the preset operating path cannot overlap, and the non-overlapping portion will form a missed area. It should be noted that, considering that the preset operating path can fully cover the target lawn care area, the lawn care area generally includes missed areas and non-missed areas.

[0129] In some embodiments, if the area of ​​the omitted region is small enough, or even smaller than a preset area threshold, it can be considered that the omitted region will not attract the user's attention and will not affect the appearance. Therefore, the omitted region with an area smaller than the area threshold can be ignored. The specific omitted area threshold can be 0.5m 2 .

[0130] In some embodiments, the aforementioned S310 can be executed based on the actual execution of the self-moving device. For example, the missed area can be determined by comparing the difference between the actual path of the self-moving device and the preset working path. Specifically, the missed area can be determined by recording the coverage of the self-moving device based on the grid map. For more information about the grid map, please refer to Figure 6 and its related description; in addition, the missed area can be determined by comparing the grass height near the moving path after moving along the preset working path. Since commercial lawn mowers have a large single-time cutting volume, when the grass height in a certain area is much higher than that in other areas, this area can be considered as a missed area. The specific comparison method can be through pictures, outlines, etc.

[0131] In some embodiments, when a lawn care task is completed for a combined area, the missing area determination component 232 can redetermine the missing areas in the lawn care area to prevent new missing areas from being generated after the lawn care task is performed on the combined area.

[0132] The preset algorithm may be an algorithm capable of clustering or classifying the missing regions. Based on the preset algorithm, at least two missing regions may be processed into a missing region set.

[0133] The missing region set is always a logical set formed by merging multiple adjacent missing regions based on a preset algorithm.

[0134] A combined area may refer to an area requiring lawn care tasks (re-mowing) based on the merged results. In some embodiments, a combined area may correspond one-to-one with a set of omitted areas. That is, omitted areas in the same omitted area set are located in the same combined area, and omitted areas in the same combined area belong to the same omitted area set. Considering that omitted areas are separated by non-missing areas, a combined area may include the set of omitted areas and the non-missing areas between any two omitted areas in the set of omitted areas.

[0135] In some embodiments, S320 may be performed based on the aforementioned preset algorithm, i.e., the preset algorithm determines a set of missing regions reflecting the clustering result based on the distribution of each missing region, and then generates a combined region based on the missing region set. For more information on generating the combined region, see Figures 4 and 5 and related content.

[0136] A compensation path can refer to a planned, covering path within the combined area that can be executed by the autonomous mobile device. Specifically, the compensation path is used to guide the autonomous mobile device to perform lawn care tasks within the combined area, thereby ensuring that any missed areas are covered.

[0137] In some embodiments, the aforementioned S330 can be performed based on a path planning algorithm. For example, a full coverage path planning algorithm can be executed on the combined area to determine a compensation path for the combined area; the compensation path guides the self-mobile device to perform full coverage cutting on the combined area. In addition, a partial coverage path planning algorithm can be executed on the combined area to determine a compensation path for the combined area; the compensation path guides the self-mobile device to perform partial coverage cutting on the combined area. The present disclosure does not limit full coverage and partial coverage; any method that can perform lawn care tasks on omitted areas in the combined area falls within the scope of protection of the present disclosure.

[0138] Furthermore, a movement path may be designed to guide the self-moving device from its current position to the combined area. While executing the movement path, the working components of the self-moving device 110 may not be in an operating state. For example, when the self-moving device 110 is a lawn mower robot, the working components may not be in an operating state while the lawn mower robot moves along the movement path, i.e., the lawn mower robot does not mow the grass. However, when the lawn mower robot moves along the compensation path, the working components of the lawn mower robot are in an operating state, i.e., the lawn mower robot mows the grass.

[0139] In some embodiments, when there are multiple combined areas, the execution order of the combined areas can be determined based on the relative distance between the current position of the mobile device 110 and the multiple combined areas, and steps S310 to S330 are repeated to determine the compensation path of each combined area and the movement path between each combined area.

[0140] In some embodiments, merging at least two of the missing regions into a combined region according to the spatial distribution characteristics includes:

[0141] Determining spatial distribution characteristics between the missing areas, wherein the spatial distribution characteristics include spatial distance, spatial density, and spatial direction;

[0142] Selecting at least two of the missing regions whose spatial distribution characteristics meet a preset spatial distribution condition as a missing region set;

[0143] The combined area is obtained according to the omitted area set, wherein the combined area covers each omitted area.

[0144] Taking spatial distance as an example, the distance between the centers of two missing areas can be determined, and the minimum distance between the boundaries of two missing areas can also be determined. When using spatial distance, the corresponding spatial distribution condition is that the spatial distance between the two missing areas is less than the preset distance threshold. That is, when the distance between two missing areas is less than the preset distance threshold, they can be regarded as a set of missing areas. Among them, the preset distance threshold is generally set to the width of a single operation. In the present disclosure, the width of a single operation can be 45cm. It should be noted that the present disclosure does not limit the statistical method of distance, and it can be specifically adaptively modified according to actual needs. For example, the distance can be the closest distance of the plane, the farthest distance of the plane, the closest distance of the projection at a specific angle / any angle, the farthest distance of the projection, etc.

[0145] For example, based on the missing regions shown in Figure 5, one can first select a missing region (e.g., C). The distances between each missing region and missing region C are then determined. Missing regions (e.g., B) whose distances are less than the spatial distance threshold are combined with missing region C as a missing region set. The distances between the combined region and each missing region are then determined. Repeating the above steps reveals that, based on spatial distribution conditions, B, C, D, and E can be considered a missing region set. Missing region A can be processed separately and considered another missing region set. In this case, regions AE are omitted, resulting in two missing region sets.

[0146] In addition, the spatial density of each missing area can be determined by a preset algorithm. The spatial distribution condition includes that the spatial density between two missing areas is less than a preset density threshold. When the spatial density between two missing areas is less than the preset density threshold, the two missing areas can be regarded as a missing area set.

[0147] In this way, the spatial distribution characteristics of the omitted regions can be taken into account, and different sets of omitted regions can be obtained using different spatial distribution characteristics and corresponding spatial distribution conditions.

[0148] In some embodiments, to improve the efficiency of lawn care tasks for combined areas, different spatial distribution features can be calculated to obtain different sets of omitted areas. For example, when using spatial distance, A can be obtained as one omitted area set, and BE as another omitted area set. For distance, if using spatial density, AC can be obtained as one omitted area set, and DE as another omitted area set. In this case, the two spatial distribution features can be compared to see which one has the shortest compensation time for AE. The spatial distribution feature with the shortest compensation time is selected as the preferred method, and the corresponding combined area is then determined by selecting the resulting spatial distribution feature.

[0149] Specifically, the controller 210 selects different spatial distribution features to obtain at least two sets of missing areas; obtains at least two combined areas based on the at least two sets of missing areas; plans the compensation path of each combined area, and calculates the compensation time corresponding to each compensation path; and determines the spatial distribution feature based on the compensation time. Further, the compensation time of the candidate combined areas under different spatial distribution features is compared, and the corresponding spatial distribution conditions are selected according to the spatial distribution feature with the shorter compensation time, and several missing areas that meet the spatial distribution conditions are selected as the missing area set. In the present disclosure, calculating the compensation time corresponding to each compensation path means calculating the time of the mobile device on the compensation path based on the compensation path under simulated conditions, wherein determining at least two sets of missing areas based on at least two preset spatial distribution conditions includes but is not limited to: a first set determination method and a second set determination method. The first set determination method and the second set determination method can use two different spatial distribution features. For example, the first set determination method can be merged based on spatial distance. The second set determination method can be merged based on spatial density.

[0150] To further describe the process, Figure 4 shows a flow chart of the process (S330). Figure 5 shows a schematic diagram of the two set determination methods determining the missing region set. The process will be described below with reference to Figures 4 and 5.

[0151] In some embodiments, the aforementioned S330 shown in FIG4 may include the following steps:

[0152] S410: Determine a first compensation path based on a first set determination method, and determine a first compensation time required to perform a lawn care task based on the first compensation path.

[0153] S420: Determine a second compensation path based on the second set determination method, and determine a second compensation time required to perform the lawn care task based on the second compensation path.

[0154] S430: Compare the first compensation time with the second compensation time.

[0155] S440: When the first compensation time is less than the second compensation time, process the at least two missing regions into one missing region set using a first set determination method.

[0156] S450: When the first compensation time is greater than the second compensation time, process the at least two missing regions into one missing region set using a second set determination method.

[0157] S460: When the first compensation time is equal to the second compensation time, process the at least two missing regions into one missing region set by using the first set determination method or the second set determination method.

[0158] The first compensation path may refer to the operating path of the candidate combination area determined based on the first set determination method. The first compensation time may refer to the length of time it takes for the self-mobile device to complete the first compensation path. The first compensation time may be determined based on the length of the first compensation path and the operating parameters of the self-mobile device. It is understood that the second compensation path may refer to the operating path of the candidate combination area determined based on the second set determination method, and the second compensation time may refer to the length of time it takes for the self-mobile device to complete the second compensation path. The second compensation time may be determined based on the length of the second compensation path and the operating parameters of the self-mobile device. The operating parameters of the self-mobile device may include but are not limited to: moving speed, turning radius, etc.

[0159] In some embodiments, when the climbing ability and anti-rolling ability of the self-moving device are limited, if no conditions are designed to merge the missing areas that meet the preset spatial distribution conditions, it is possible that the height difference between the two missing areas in the same missing area set will be too large, which may affect the passability of the self-moving device. Therefore, before processing at least two missing areas whose spatial distribution characteristics meet the preset spatial distribution conditions into one missing area set, it includes: judging whether the blocking condition is met between at least two of the missing areas; when the blocking condition is met, the at least two missing areas are divided into different missing area sets, and when the blocking condition is not met, the at least two missing areas can be divided into the same missing area set. In the present disclosure, the blocking condition includes one or more of the following conditions: the height difference between the missing areas is less than the preset height threshold; there are impassable obstacles between the missing areas; the cutting parameters between the missing areas are different.

[0160] For example, even if the spatial distribution characteristics of the missing area A and the missing area B meet the spatial distribution conditions, if there is an obstacle between the missing area A and the missing area B, then the compensation efficiency of the self-moving device will be greatly affected. Therefore, it is possible to consider placing the missing area A and the missing area B in two different missing area sets; if the cutting parameters of the missing area A and the missing area B are different, then the cutting parameters will be continuously adjusted when compensating along the compensation path, which will also greatly affect the compensation efficiency of the self-moving device. Therefore, it is possible to consider placing the missing area A and the missing area B in two different missing area sets. The cutting parameters in this disclosure include cutting height, single cutting amount, cutting speed, etc. If the height of the missing area A and the missing area B is greater than the preset height threshold, then it may cause slipping when compensating along the compensation path, which will also greatly affect the compensation efficiency of the self-moving device. Therefore, it is possible to consider placing the missing area A and the missing area B in two different missing area sets. In this disclosure, the preset height threshold is 25cm.

[0161] In some embodiments, as shown in FIG4 , S410 may further include the following steps:

[0162] S411 . Determine a plurality of first combination areas based on a first set determination method, and determine a first compensation path for each first combination area.

[0163] S412: Calculate a first total time required for the self-moving device to perform lawn care along the plurality of first compensation paths, and use the first total time as a first compensation time.

[0164] In some embodiments, as shown in FIG4 , S420 may further include the following steps:

[0165] S421: Determine a plurality of second combination areas based on a second set determination method, and determine a second compensation path for each second combination area.

[0166] S422: Calculate a second total time required for the self-moving device to perform lawn care along the plurality of second compensation paths, and use the second total time as a second compensation time.

[0167] To further illustrate the specific determination process of the first set determination method and the second set determination method, FIG5 is described below.

[0168] In this way, the total time for lawn care work on all the missed areas can be calculated, and the collective determination method with the shortest total time is used as the final method.

[0169] In some embodiments, the first set determination method can be understood as selecting the missing areas within the lawn care area using a rectangle without duplication. Each selected area can be configured as a missing area set. Considering that the present disclosure employs a bow-shaped full coverage path planning algorithm, the aforementioned preset pattern is generally configured as a rectangle with a width that is an integer multiple of the width of a single operation of the self-moving device.

[0170] After determining the missing region set using any of the above set determination methods, a combined region can be determined based on the missing region set. In some embodiments, determining the combined region based on the missing region set includes: determining the boundaries of each missing region in the missing region set; and performing boundary fitting on the boundaries of each missing region to obtain the combined region.

[0171] Boundary fitting can refer to determining a shape that includes all the missing regions in the missing region set based on the missing region set, and using this shape as the combined region. For example, the first framed region 510 and the second framed region 520 can be directly used as the rectangular fitting result and used as the combined region.

[0172] Specifically, a bounding rectangle is drawn along different directions along the boundaries of each missing area in the missing area set, and the bounding rectangle covers all missing areas in the missing area set;

[0173] Determine the smallest circumscribed rectangle among the circumscribed rectangles according to geometric features, wherein the geometric features include area, side length, and aspect ratio;

[0174] The area covered by the minimum circumscribed rectangle is used as the combined area.

[0175] In the present disclosure, an initial direction may be selected, and 18 different circumscribed rectangles may be obtained in sequence with each 10° being a direction.

[0176] In some embodiments, in order to minimize the area of ​​the combined area, the present disclosure may use geometric features to determine a minimum bounding rectangle. The minimum bounding rectangle refers to the minimum rectangle that can contain all the missing areas in the missing area set. In some embodiments, the minimum bounding rectangle can be generated based on a preset direction. In some embodiments, the minimum bounding rectangle can be generated based on an arbitrary direction. When generated based on an arbitrary direction, multiple bounding rectangles can be generated. In the present disclosure, the areas of the multiple bounding rectangles are sorted, and the bounding rectangle with the smallest area is used as the minimum bounding rectangle. Similarly, the perimeters of the multiple bounding rectangles can also be sorted, and the bounding rectangle with the smallest perimeter is used as the minimum bounding rectangle.

[0177] According to the method of making the minimum circumscribed rectangle, the combined area corresponding to the missing area set is obtained.

[0178] In some embodiments, the minimum bounding rectangle of the set of missing regions may be calculated based on a minimum bounding rectangle-related algorithm. For example, the minimum bounding rectangle may be determined based on a rotating calipers algorithm, a minimum area rectangle algorithm, a randomized incremental method, or a related algorithm.

[0179] After obtaining a relatively appropriate combined area, a compensation path of the combined area needs to be planned. The compensation path can cover the missed areas. When the mobile device moves along the compensation path, all the missed areas in the combined area can be compensated.

[0180] Thus, based on the missing area path planning method provided by the embodiments of the present disclosure, the self-mobile device can promptly identify missing areas and execute lawn care tasks, thereby improving the completion rate of the task. In addition, a compensation path can be constructed based on the clustering results of the missing areas, so that each individual missing area can be processed in a single lawn care task. Compared with executing lawn care tasks for each missing area separately, this reduces the operation time and improves overall operation efficiency.

[0181] Specifically, as shown in the compensation operation path diagram in Figure 7, multiple circumscribed rectangles can be generated in any direction, and the circumscribed rectangle 71 and the circumscribed rectangle 72 both cover the omitted areas 73 and 74. Then, the area of ​​each circumscribed rectangle is determined, and the circumscribed rectangle with the smallest area is identified as the minimum circumscribed rectangle. In Figure 7, the minimum circumscribed rectangle is circumscribed rectangle 72. Of course, the perimeter of each circumscribed rectangle can also be determined, and the circumscribed rectangle with the smallest perimeter is identified as the minimum circumscribed rectangle. This disclosure does not limit this.

[0182] However, the above method requires many turns, which may cause the autonomous vehicle to wear out the lawn. Therefore, after obtaining a relatively appropriate combined area, it is necessary to plan a compensation path for the combined area. This compensation path can cover the missed areas. When the autonomous vehicle moves along the compensation path, it can compensate for all the missed areas in the combined area.

[0183] Specifically, in the present disclosure, after determining the minimum bounding rectangle 72 as the bounding rectangle, the long side 721 and short side 722 of the bounding rectangle can be determined. In the present disclosure, the long side 721 is longer than the short side 722. After determining the minimum bounding rectangle 72, a compensation path for performing the lawn care task on the combined area needs to be determined. In the present disclosure, the compensation path guides the self-moving device to perform the lawn care task on the combined area. Furthermore, a movement path can be designed, which is the shortest straight line from the current position of the self-moving device to the combined area. This ensures that the self-moving device enters the combined area as quickly as possible. This disclosure focuses on the compensation path. In order to make the compensation path more reasonable and ensure that the self-moving device can perform lawn care tasks faster along the compensation path, the present disclosure takes into account that the speed of the self-moving device walking in a straight line is greater than the turning speed. For the convenience of explanation, the compensation path in the present disclosure includes two parts. The first part is a plurality of straight paths 75. The spacing between the plurality of straight paths 75 can be fixed. The second part is a turning path 76. The turning path 76 connects two adjacent straight paths 75. The present disclosure uses the direction parallel to the long side as the direction of the straight path 75. The present disclosure does not limit the turning path 76. Any path that can connect the straight paths 75 to each other and can ensure that the missed area 73 or the missed area 74 near the short side can be cleared can be used as the turning path 76.

[0184] Compared to not designing a compensation path, the compensation path of the present disclosure reduces the number of turns. Thus, based on the path planning method based on missed areas provided by the embodiments of the present disclosure, the self-mobile device can promptly identify missed areas and perform lawn care tasks to improve the completion rate of the task. In addition, the compensation path can be constructed based on the clustering results of the missed areas, so that each individual missed area can be processed in a single lawn care task. Compared to performing lawn care tasks for each missed area separately, this reduces the operation time and the degree of wear on the lawn, thereby improving overall operation efficiency.

[0185] The present disclosure provides a method for determining a turning path, including: determining the position of a minimum bounding rectangle 72 in a lawn care area 7. In the present disclosure, the minimum bounding rectangle 72 may be located in the middle of the lawn care area 7 or at the edge of the lawn care area 7. If the outside of the lawn care area 7 is an area inaccessible to a self-moving device, the position of the minimum bounding rectangle 72 in the lawn care area 7 will affect the type of the turning path 76. Specifically, if the minimum bounding rectangle 72 is located in the middle of the lawn care area 7, the turning path can exceed the minimum bounding rectangle 72 without worrying about the self-moving device colliding with the inaccessible area outside the lawn care area 7. If the minimum bounding rectangle 72 is located at the edge of the lawn care area 7, the turning path cannot exceed the minimum bounding rectangle 72, and collision with the inaccessible area outside the lawn care area 7 must be avoided.

[0186] In this way, the highest efficiency of the self-moving device along the compensation path can be guaranteed.

[0187] However, in some cases, if the user has high requirements for the aesthetics of the lawn care area, the above method will cause the compensation path to intersect with the preset working path. In layman's terms, the pattern generated by the mobile device along the compensation path in the lawn care area is inconsistent with the pattern generated along the preset working path in the lawn care area.

[0188] In addition, a compensation path can also be designed. The compensation path is the same as the above, except that the direction of the straight path needs to completely coincide with the preset working path. That is, the compensation path covering the combined area is planned, including:

[0189] A preset operation path encompassed by the minimum circumscribed rectangle is determined; the straight portion of the preset operation path within the minimum circumscribed rectangle is defined as the straight path. Since the present disclosure assumes that the preset operation path is a bow-shaped path, the preset operation path necessarily has a straight portion and a turning portion. To ensure a completely consistent pattern, the present disclosure can control the straight portion of the compensation path to completely overlap with the straight portion of the preset operation path. In this case, the pattern produced by the self-moving device along the compensation path in the lawn care area is consistent with the pattern produced along the preset operation path in the lawn care area.

[0190] This way the aesthetics can be improved.

[0191] In addition, a compensation path can also be designed. The compensation path is the same as the above content, except that the direction of the straight path needs to partially overlap with the preset working path. That is, the compensation path covering the combined area is planned, including:

[0192] The straight direction of the straight portion of the preset working path is determined; and the direction of the straight path of the compensation path is determined based on the straight direction of the straight portion of the preset working path. Since the preset working path is assumed in the present disclosure to be a bow-shaped path, the preset working path necessarily has a straight portion and a turning portion. To ensure the direction of the pattern is consistent, the present disclosure can control the straight path of the compensation path to completely overlap with the straight portion of the preset working path. In this case, the pattern produced by the self-moving device along the compensation path in the lawn care area is consistent in direction with the pattern produced along the preset working path in the lawn care area.

[0193] Example grid map

[0194] In some embodiments, a mobile device can determine the missed areas and non-missed areas in a lawn care area based on a raster map. Raster maps, also known as raster images or raster data, are a pixel-based map representation method. Raster maps divide geographic space into regular grid cells, each of which is called a pixel, and each pixel contains a specific value or attribute. In the present disclosure, the states of the grid cells include an un-lawn-care state and a lawn-care state, wherein the un-lawn-care state indicates that the working component is not covered, and the lawn-care state indicates that the working component is covered.

[0195] In some embodiments, when determining a missing area based on a grid map, a grid map of a lawn care area may be first determined. In a target lawn care task, the status of multiple grid cells covered by a working component when the mobile device performs the lawn care task is updated from an uncared-for state to a cared-for state, and the area consisting of the multiple cared-for grid cells is defined as a cared-for area in the target lawn care area.

[0196] FIG6 is a schematic diagram of a grid map provided by an exemplary embodiment of the present disclosure.

[0197] As shown in Figure 6, as the self-mobile device moves, it updates the state of the grid cells covered by the working component to the "lawn-tended" state based on its own positioning information. In Figure 6, the "lawn-tended" state is configured as a diagonal stripe pattern, while the "untended" state can be configured as a blank pattern (i.e., no pattern within the pixel).

[0198] The lawn care area can be determined based on the outline of interconnected grid cells in the lawn care state. As shown in Figure 6, the lawn care area in Figure 6 is formed by grid cells in the lawn care state, and lawn care area 610 also includes a plurality of grid cells in the unlawn care state.

[0199] In some embodiments, multiple missing areas are determined based on the status of multiple grid cells in lawn care area 610. Specifically, if there are grid cells in an unmaintained state in areas 620 and 630 in lawn care area 610 shown in FIG6 , areas 620 and 630 can be configured as missing areas.

[0200] In some embodiments, when the missing region includes multiple grid cells, it can be considered that the multiple grid cells corresponding to each missing region are in an unmaintained state, and the grid cells in the missing region are interconnected. That is, the aforementioned region 620 includes three consecutive grid cells in an unmaintained state.

[0201] For the sake of convenience, in this disclosure, performing lawn care tasks along the compensation path from a mobile device is referred to as back-mowing.

[0202] In some embodiments, before determining the missing area, the controller 210 can divide the lawn care area into multiple first sub-areas based on a grid map, so that the mobile device can sequentially perform lawn care tasks for each of the first sub-areas. In the present disclosure, the first sub-area where the mobile device 110 is located is the area where the lawn care task is required. The controller 210 controls the mobile device 110 to perform the lawn care task for the first sub-area in which it is located. After the mobile device 110 completes the lawn care task for the current first sub-area, the mobile device performs re-mowing on the missing area in the current first sub-area. After re-mowing is completed, the controller 210 controls the mobile device 110 to perform the lawn care task for the next first sub-area, and then re-mowing on the missing area in the next first sub-area, repeating the above steps until the lawn care task for the entire lawn care area and re-mowing of the combined areas in the lawn care area are completed. The above method, by partitioning the lawn care area and sequentially performing lawn care tasks for each first sub-area and re-mowing the combined areas, can reduce the problem of large distance span when re-mowing the combined areas in the lawn care area.

[0203] In one embodiment, the aforementioned first sub-area division can also be performed based on an island area. Specifically, the lawn care area can be divided into multiple first sub-areas along two circumferential tangent lines of the island area. The two circumferential tangent lines of the island area are parallel to the directions of a portion of the preset operation path in the lawn care area, and the island area is configured to prohibit the autonomous mobile device from entering.

[0204] Island regions can be defined as a collection of grid cells in a raster map that represent obstacles. The grid cells corresponding to island regions are completely filled with a solid black color. In a raster map, grid cells can be further divided into foreground cells, which represent obstacles, and background cells, which represent non-obstacles. Connected regions composed of foreground pixels can be extracted using algorithms such as connected component analysis. These connected regions are called island regions, representing the location and shape of obstacles.

[0205] A circumtangent line is a line that is tangent to a given shape (such as a circle, ellipse, or polygon) and tangent to the shape's curve at the point of tangency. A circumtangent line is tangent to the shape's curve at only one point and does not pass through the shape. The circumtangent lines of an island region are line segments extending along the edge of the island region.

[0206] The above-described zoning process can also be illustrated in FIG6 . As shown in FIG6 , the lawn care area may include an island area 640 . Two tangent lines AA and BB can be drawn along the vertical direction of the figure to form three first sub-areas: a first sub-area 650 , a first sub-area 660 , and a first sub-area 670 enclosed by AA and BB. The first sub-area 650 is located to the left of AA, and the second sub-area 660 is located to the right of BB.

[0207] In some embodiments, the first sub-area can also be divided based on the height difference between grid cells. Specifically, the height difference between each two grid cells can be determined based on a grid map of the lawn care area. When the height difference is greater than a preset value, the two grid cells are divided into different first sub-areas. In some embodiments, the height difference can be determined based on the height adjustment capability of the mobile device.

[0208] In some embodiments, the first sub-area can be partitioned into multiple levels to ensure accurate identification of missed areas. Specifically, multiple first sub-areas can be determined within the lawn care area, each of which can be divided into at least two second sub-areas according to a preset path width. The self-moving device can be controlled to move within the second sub-areas along a preset operation path. After completing a second sub-area, missed areas within the second sub-area are determined. For example, upon completing a lawn care task in a current second sub-area, missed areas within the second sub-area are determined to avoid excessively long movement paths during the compensation process.

[0209] In some embodiments, the second sub-area can be determined based on a preset path width. For example, when the width of the first sub-area is an integer multiple of the preset path width, the first sub-area is divided into multiple second sub-areas, each with a width equal to the preset path width. For another example, when the width of the first sub-area is not an integer multiple of the preset path width, the first sub-area is divided into at least one second sub-area with a width equal to the preset path width and one second sub-area with a width less than the preset path width. The preset path width can be an integer multiple of the width of a single operation of the self-moving device.

[0210] It should be understood that the term "and / or" in this document simply 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. Furthermore, the character " / " in this document generally indicates that the related objects are in an "or" relationship.

[0211] It should be understood that in the various embodiments of the present disclosure, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0212] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0213] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the objectives of the disclosed solution based on actual needs.

[0214] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0215] In the above embodiments, all or part of the embodiments can be implemented through software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present disclosure are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device, a core network device, an operation and maintenance management (OAM), or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media. Available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid state disks (SSDs)). The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0216] The above are only specific embodiments of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A path planning method, characterized in that: The method is applied to a self-moving device having a working component, wherein the self-moving device is configured to move along a preset working path and perform lawn care tasks via the working component during movement, the method comprising: Determining a missed area, wherein the missed area is formed by the self-moving device deviating from the preset working path and / or the working component not covering it; merging at least two of the missing areas into a combined area according to spatial distribution characteristics; A compensation path covering the combined area is planned, wherein the compensation path is configured to guide the self-moving device to continuously move in the combined area, and the working component performs the lawn care task during the movement.

2. The method according to claim 1, characterized in that The merging of at least two of the missing areas into a combined area according to the spatial distribution characteristics includes: Determining spatial distribution characteristics between the missing areas, wherein the spatial distribution characteristics include one or more of spatial distance, spatial density, and spatial direction; Selecting at least two of the missing regions whose spatial distribution characteristics meet a preset spatial distribution condition as a missing region set; The combined area is obtained according to the missing area set, wherein the combined area covers the at least two missing areas.

3. The method according to any one of the above claims, characterized in that: The spatial distribution conditions include: The spatial distance between the two missed areas is less than a preset distance threshold.

4. The method according to any one of the above claims, characterized in that: The obtaining the combined area according to the set of missing areas includes: Determining a boundary of each missing region in the missing region set; Boundary fitting is performed on the boundaries of each missing region to obtain the combined region.

5. The method according to any one of the above claims, characterized in that: The performing boundary fitting on the boundaries of each missing region to obtain the combined region includes: Draw a circumscribed rectangle along different directions along the boundaries of each missing area in the missing area set, wherein the circumscribed rectangle covers all missing areas in the missing area set; Determine the smallest circumscribed rectangle among the circumscribed rectangles according to geometric features, wherein the geometric features include area, side length, and aspect ratio; The area covered by the minimum circumscribed rectangle is used as the combined area.

6. The method according to any one of the above claims, characterized in that: The step of determining the minimum bounding rectangle among the bounding rectangles according to the geometric features includes: The smallest circumscribed rectangle among all circumscribed rectangles is used as the minimum circumscribed rectangle; or The circumscribed rectangle with the smallest side length among all circumscribed rectangles is used as the minimum circumscribed rectangle; or The circumscribed rectangle with the largest aspect ratio among the circumscribed rectangles is used as the minimum circumscribed rectangle.

7. The method according to any one of the above claims, characterized in that: The compensation path includes a plurality of straight paths and a plurality of turning paths, and adjacent straight paths are connected through the turning paths.

8. The method according to any one of the above claims, characterized in that: The planning of the compensation path covering the combined area includes: Determine the long side and the short side of the minimum circumscribed rectangle, wherein the length of the long side is greater than the length of the short side; The straight path is determined according to the long side.

9. The method according to any one of the above claims, characterized in that: The determining the straight path according to the long side includes: determining the direction of the long side; The direction of the straight path is determined according to the direction of the long side.

10. The method according to any one of the above claims, characterized in that: The planning of the compensation path covering the combined area includes: Determining a preset operation path covered by the minimum circumscribed rectangle; The straight portion of the preset operation path within the minimum circumscribed rectangle is used as the straight path.

11. The method according to any one of the above claims, characterized in that: The planning of the compensation path covering the combined area includes: determining a straight direction of the straight portion of the preset operation path; The direction of the straight path of the compensation path is determined according to the straight direction of the straight portion of the preset working path.

12. The method according to any one of the above claims, characterized in that: The preset operation path guides the self-moving device to move within the lawn care area; The further step includes: determining a position of the circumscribed rectangle in the lawn care area; A type of the turning path is determined based on the position.

13. The method according to any one of the above claims, characterized in that: Also includes: Select different spatial distribution features to obtain at least two sets of missed regions; Obtaining at least two combined regions based on at least two missing region sets; Planning compensation paths for each combined area, and calculating compensation time corresponding to each compensation path; The spatial distribution characteristics are determined according to the compensation time.

14. The method according to any one of the above claims, characterized in that: The determining the spatial distribution feature according to the compensation time includes: The compensation times are sorted, and the spatial distribution characteristics are determined according to the sorting result.

15. The method according to any one of the above claims, characterized in that: The selecting of different spatial distribution features to obtain at least two sets of missing regions includes: Determining whether a blocking condition is satisfied between at least two of the missing areas; When the blocking condition is met, at least two of the missing areas are divided into different missing area sets.

16. The method according to any one of the above claims, characterized in that: The blocking conditions include one or more of the following conditions: The height difference between the omitted areas is greater than a preset height threshold; There are impassable obstacles between the omitted areas; The cutting parameters between the omitted regions are different.

17. The method according to any one of the above claims, characterized in that: Also includes: determining the area of ​​the missing region; Ignore missed regions whose area is smaller than the area threshold.

18. A self-propelled device, characterized in that: include: a work component configured to perform lawn care tasks; A moving component is configured to drive the working component to move, so that the working component performs the lawn care task while moving; as well as A processor is configured to be connected to the moving component and the working component to implement the method described in any one of claims 1 to 16.

19. The self-moving device according to claim 18, characterized in that: The working assembly includes a cutting assembly; The processor is configured to plan an operating path for the self-moving device in the lawn care area based on a map of the lawn care area, and output a first instruction to the cutting component and the moving component to control the self-moving device to autonomously traverse the lawn care area along the operating path and mow the lawn in one step, wherein the mowing in one step is achieved by synchronously chopping or collecting grass during mowing.

20. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 17.

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