Operation path planning method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of path planning, and provides an operation path planning method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an operation task corresponding to a robot, determining an operation range according to the operation task, and carrying out the path planning of the robot based on the position of a charging point in the operation range and the operation task. Obtaining an initial operation path; gradient road sections in the initial operation path are obtained, and the electric quantity state of the robot in each gradient road section is predicted; if the electric quantity state of the robot on any slope road section is not matched with a preset target electric quantity state, path planning is carried out on the robot again based on the charging point position and the operation task in the operation range, and a new initial operation path is obtained; and under the condition that the electric quantity state of the robot at each gradient road section is matched with the preset target electric quantity state, the initial operation path is used as the target operation path, so that the robot fully considers the influence of the gradient on energy consumption and energy recovery in the path planning stage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of path planning, and in particular to a work path planning method and device, an electronic device, and a storage medium. BACKGROUND

[0002] With the wide application of mobile work equipment such as agricultural robots, garden maintenance robots, and warehouse inspection robots, robots often need to automatically plan driving paths and work paths according to task requirements in a large range, multiple processes, and long time work process. Existing path planning methods mostly take the shortest geographical position or the optimal time as the target, only combine the work task and the terrain information to generate a path, and do not fully consider the energy consumption characteristics of the robot under different terrain conditions.

[0003] In a complex terrain environment, especially in a work scene with a large slope, the driving energy consumption and energy recovery characteristics of the robot will be significantly different with the change of the slope. For example, the robot needs additional driving power to overcome the slope resistance on an uphill road section, and if the power is insufficient, it may cause climbing failure or stop halfway. On a downhill road section, since most small and medium-sized robots use motor energy recovery to maintain uniform speed, if the battery state of charge is too high, it cannot continue to absorb the recovered energy, which is easy to cause battery overvoltage, heating, and even damage. SUMMARY

[0004] Therefore, the embodiments of the present application provide a work path planning method and device, an electronic device, and a storage medium to solve the problem that the existing technology does not fully consider the energy consumption characteristics of the robot under different terrain conditions, which leads to the fact that the planned work path cannot match the power change in the actual work process, affecting the robot operation.

[0005] The first aspect of the embodiments of the present application provides a work path planning method, which comprises: obtaining a work task corresponding to a robot, determining a work range according to the work task, planning a path for the robot based on the charging point position in the work range and the work task to obtain an initial work path; obtaining a slope section in the initial work path and predicting the power state of the robot in each slope section; if the power state of the robot in any slope section does not match the target power state set in advance, planning a path for the robot again based on the charging point position in the work range and the work task to obtain a new initial work path; and in the case where the power state of the robot in each slope section matches the target power state set in advance, taking the initial work path as a target work path. In a second aspect, the embodiment of the present application provides a work path planning device, which comprises: a planning module, configured to acquire a work task corresponding to a robot, determine a work range according to the work task, plan a path for the robot based on a charging point position in the work range and the work task, and obtain an initial work path; a prediction module, configured to acquire a slope section in the initial work path, and predict an electric quantity state of the robot on each slope section; the planning module is further configured to, if the electric quantity state of the robot on any slope section does not match a preset target electric quantity state, plan a path for the robot again based on the charging point position in the work range and the work task, and obtain a new initial work path; and in the case that the electric quantity state of the robot on each slope section matches the preset target electric quantity state, the initial work path is taken as a target work path.

[0006] In a third aspect, the embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.

[0007] In a fourth aspect, the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0008] Compared with the prior art, the embodiment of the present application has the beneficial effects that: the method in the embodiment of the present application acquires a work task corresponding to a robot, determines a work range according to the work task, plans a path for the robot based on a charging point position in the work range and the work task, and obtains an initial work path; acquires a slope section in the initial work path, and predicts an electric quantity state of the robot on each slope section; if the electric quantity state of the robot on any slope section does not match a preset target electric quantity state, the method plans a path for the robot again based on the charging point position in the work range and the work task, and obtains a new initial work path; and in the case that the electric quantity state of the robot on each slope section matches the preset target electric quantity state, the method takes the initial work path as a target work path, which can make the robot fully consider the influence of the slope terrain on energy consumption and energy recovery in the path planning stage, realize dynamic prediction and adjustment of the electric quantity state of the robot, ensure sufficient power when climbing and reasonable energy recovery space when descending, and avoid the problem that the prior art does not fully consider the energy consumption characteristics of the robot under different terrain conditions, which leads to that the planned work path cannot match the electric quantity change in the actual work process, and affects the operation of the robot. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0010] Figure 1 is a flowchart of a work path planning method provided by an embodiment of the present application; Figure 2 is a flowchart of another work path planning method provided by an embodiment of the present application; Figure 3 is a flowchart of still another work path planning method provided by an embodiment of the present application; Figure 4 is a flowchart of another work path planning method provided by an embodiment of the present application; Figure 5 is a structural diagram of a work path planning device provided by an embodiment of the present application; Figure 6 is a structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0011] In the following description, specific details such as specific system structures, techniques, etc. are presented in order to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits and methods are omitted in order not to obscure the description of the present application with unnecessary details.

[0012] A work path planning method and device according to an embodiment of the present application will be described in detail below with reference to the drawings.

[0013] Figure 1 is a flowchart of a work path planning method provided by an embodiment of the present application, as shown in Figure 1 , the method comprises: S101, obtaining a work task corresponding to a robot, determining a work range according to the work task, and planning a path for the robot based on the position of a charging point in the work range and the work task to obtain an initial work path; S102, obtaining a slope section in the initial work path, and predicting the power state of the robot on each slope section; S103, if the power state of the robot on any slope section does not match the pre-set target power state, re-planning the path of the robot based on the charging point position in the work range and the work task to obtain a new initial work path; S104, in the case that the power state of the robot on each slope section matches the pre-set target power state, taking the initial work path as the target work path.

[0014] It can be understood that the work path planning method provided by the embodiments of the present application is applied to a robot or a controller for controlling the robot, and the robot includes but is not limited to an agricultural robot, a garden maintenance robot, and a warehouse inspection robot.

[0015] Firstly, the work range is determined according to the work task corresponding to the robot, the work task including at least one work procedure and a corresponding work site, such as a spraying, cleaning, pruning or fertilizing work procedure, and a work site corresponding to each work procedure.

[0016] After obtaining the work task, the work range corresponding to the work task can be determined according to the work task, the work range including all work sites, and the work range being used to limit the movement and work area of the robot in the current task cycle.

[0017] It can be understood that after the work range is determined, the path of the robot is planned based on the charging point position in the work range and the work task to obtain an initial work path, the initial work path taking into account the starting site of the robot (that is, the current position of the robot), the ending site (that is, the parking position or charging base station to which the robot needs to return after completing all work), each work site in the work range, and the power of the robot, the charging point position and other factors. In the path planning, the controller evaluates different path combinations according to the execution order of each work procedure, the distance of the travel path and the corresponding travel energy consumption, to select the optimal route scheme between energy consumption and task completion efficiency.

[0018] In addition, the current power state of the robot is also considered in the planning process. When it is predicted that the remaining power after a certain path section may be lower than the pre-set safety margin, a charging point node in the work range is preferentially inserted before the path section, so as to generate an initial work path that meets the power constraint condition.

[0019] Therefore, the initial work path not only contains the travel route between each work site, but also contains one or more charging point positions for energy supplement, so as to ensure that the robot can successfully complete all work tasks within a safe power range.

[0020] That is, the application generates an initial planning path according to the starting point, ending point and each work point in the work range of the robot; predicts the expected remaining power of the robot after passing through each road segment according to the power consumption requirement of the robot in each work procedure and the driving energy consumption of the robot in each road segment in the initial planning path; when the expected remaining power is lower than the preset safety margin, selects a charging point from the charging point positions in the work range before the road segment as an intermediate node to insert into the initial planning path to obtain an initial work path, wherein after inserting the charging point, the controller updates and recalculates the path to obtain the initial work path considering the charging point. The initial work path contains not only the work segments and driving segments required for the robot to complete the work task, but also the charging points automatically inserted to ensure power safety, thereby ensuring that the robot can continuously operate throughout the work cycle.

[0021] In some examples, after generating the initial work path, in order to further improve the accuracy of path planning and the safety of the work process, the application embodiment further acquires slope road segment information in the initial work path, which is an uphill road segment or a downhill road segment that meets a preset slope threshold.

[0022] Specifically, the controller (or the robot itself) identifies the uphill road segment and the downhill road segment that meet the preset slope threshold according to the terrain data in the initial work path; then combines the current power of the robot, the battery capacity, the driving motor efficiency and the energy recovery parameters to calculate the energy consumption or energy recovery of the robot when passing through each slope road segment, thereby obtaining the expected power state of the robot in each slope road segment.

[0023] Through energy state prediction of the slope road segment, the risk of insufficient power in the uphill segment or excessive power in the downhill segment can be identified in advance, providing a basis for subsequent power adjustment, pre-consumption action or path re-planning.

[0024] In some examples, if the power state of the robot in any slope road segment does not match the preset target power state (for example, the power state is higher than the upper limit of the target power state in the downhill road segment, or the power state is lower than the lower limit of the target power state in the uphill road segment), the robot is re-planned a path based on the charging point positions in the work range and the work task to obtain a new initial work path; the charging node or the work order is adjusted in the new path planning to obtain a new initial work path, so that the robot has a power level that meets the target power state in the subsequent slope road segment.

[0025] In the case where the power state of the robot in each slope road segment matches the preset target power state, the initial work path is taken as the target work path, and the robot is controlled to perform the corresponding work task according to the target work path.

[0026] According to the technical solution provided in this application, the robot's corresponding task is obtained, the work range is determined based on the task, and path planning is performed on the robot based on the charging point locations and the task within the work range to obtain an initial work path. The slope segments in the initial work path are obtained, and the robot's battery status at each slope segment is predicted. If the robot's battery status at any slope segment does not match the pre-set target battery status, the robot's path is re-planned based on the charging point locations and the task within the work range to obtain a new initial work path. If the robot's battery status at each slope segment matches the pre-set target battery status, the initial work path is used as the target work path. This solution enables the robot to fully consider the impact of slope terrain on energy consumption and energy recovery during the path planning stage, achieving dynamic prediction and adjustment of the robot's battery status, ensuring sufficient power when going uphill and reasonable energy recovery space when going downhill. This avoids the problem in the prior art where the robot's energy consumption characteristics under different terrain conditions are not fully considered, leading to a planned work path that cannot match the actual battery changes during operation, thus affecting robot operation.

[0027] In some examples, such as Figure 2 As shown, the slope segments in the initial operation path are obtained, and the robot's battery status is predicted for each slope segment, including: S201. Calculate the change in the robot's power consumption when passing through each slope section. S202. Based on the change in battery level and the battery level of the robot before it enters each slope section, predict the battery status of the robot in the slope section.

[0028] Specifically, based on terrain data in the initial work path, the controller identifies uphill and downhill sections that meet preset slope thresholds and acquires the length, slope angle, and road surface characteristics of each slope section. For uphill sections, the controller calculates the energy consumption required to overcome slope resistance based on information such as robot mass, drive power, and slope angle, and uses this energy consumption as the change in battery power. For downhill sections, the controller calculates the recoverable energy based on the motor's energy recovery capability and battery recovery efficiency, and uses this calculated recoverable energy as the change in battery power. By calculating the energy change for each slope section, the energy consumption or energy recovery of the robot under different terrain conditions can be obtained.

[0029] The controller obtains the predicted battery level of the robot at the starting point of each slope section, and combines it with the energy change results obtained in step S201 to predict the battery level of the robot within and at the end of the slope section, which serves as the battery status of the robot in the slope section.

[0030] Through the above steps, the controller can identify the power risk of the robot on different slope sections in advance, provide a basis for subsequent path adjustment, charging point insertion or power pre-consumption operation, and thus improve the safety and rationality of the overall path planning.

[0031] In some examples, as shown in Figure 3 The work path planning method provided by the application further includes: S301, when the power state is higher than the target power state, the power difference between the power state and the target power state is obtained; S302, the power difference is compared with the pre-set difference threshold value, and if the power difference is greater than the difference threshold value, it is determined that the power state of the robot on the slope section does not match the pre-set target power state.

[0032] It can be understood that the robot will recover energy through the motor to maintain uniform speed or stable operation in the downhill section. When the slope is large, the downhill distance is long, or the initial power of the robot when entering the downhill section is too high, the amount of energy recovery may exceed the safe recovery range of the battery. When the power state is higher than the target power state, it indicates that the robot has recovered more energy in the slope section. In order to more accurately determine whether such energy recovery will affect the safety of the battery, the application further compares the amount of energy recovery with the maximum energy recovery capacity allowed by the battery.

[0033] Specifically, when the power state is higher than the target power state, the power difference between the power state and the target power state is obtained, and the power difference is used to reflect the magnitude of the energy recovery of the robot in the downhill process exceeding the target power state. When the power difference is less than or equal to the difference threshold value, it indicates that the amount of energy recovery of the robot in the slope section is within an acceptable range and will not affect the safety of the battery. At this time, it is determined that the power state of the robot on the slope section matches the pre-set target power state. When the power difference is greater than the difference threshold value, it indicates that the robot has excessive energy recovery in the slope section, which may cause risks such as battery overvoltage or temperature rise, and the power state of the robot on the slope section does not match the pre-set target power state.

[0034] Therefore, in the latter case, the controller determines that the power state of the robot on the slope section does not match the pre-set target power state, and can further trigger corresponding power adjustment measures, such as performing a pre-consumption action before entering the slope section, or re-planning the path to reduce the power level before entering the slope section, so as to ensure the safety of the energy recovery process.

[0035] In some examples, as shown in Figure 4 The work path planning method provided by the application further includes: S401, compare the state of charge with the minimum charge threshold if the state of charge is less than the target state of charge; S402, if the state of charge is less than the minimum charge threshold, determine that the state of charge of the robot on the slope section does not match the pre-set target state of charge.

[0036] It can be understood that the robot needs greater driving force to overcome the slope resistance when driving on an uphill section, and the energy consumption is significantly higher than driving on flat ground. When the slope is too large or the uphill section is too long, and the state of charge of the robot before entering the uphill section is low, it may cause the robot to be unable to complete the uphill driving, or even to be stalled in the middle of the slope.

[0037] Therefore, when the state of charge is detected to be lower than the lower limit of the target state of charge, the state of charge is further compared with the minimum charge threshold: when the state of charge is higher than the minimum charge threshold, it indicates that the robot still has the ability to complete the uphill driving, and can continue to work along the current path, and at this time it is determined that the state of charge of the robot on the slope section matches the pre-set target state of charge; when the state of charge is lower than the minimum charge threshold, it indicates that the robot has a risk of insufficient power on the uphill section. In the latter case, the controller determines that the state of charge of the robot on the slope section does not match the pre-set target state of charge, and can further trigger path adjustment measures, such as inserting a charging node before entering the uphill section or re-planning the path, to ensure that the robot has sufficient driving power on the uphill section, thereby ensuring the continuity and safety of the work task.

[0038] In some examples, after re-planning the initial work path of the robot based on the charging point position in the work range and the work task, the method further comprises: if the state of charge of the robot on any uphill slope section does not match the pre-set target state of charge under the re-planned initial work path, inserting an uphill pre-consumption in the path planning process to actively consume the state of charge of the robot before entering the uphill slope section.

[0039] Specifically, the uphill pre-consumption action can include: increasing the uphill driving distance before the uphill slope section, increasing the high-power work procedure, or performing a short-time load operation, so that the state of charge of the robot is reduced to within the target state of charge, thereby having a matched energy level with the target state of charge when entering the uphill slope section, avoiding the situation of insufficient driving force or unreasonable power distribution due to the deviation of the state of charge. In the above-mentioned manner, the matching relationship between the power and the terrain can be further optimized after re-planning the path, to ensure that the robot can still maintain stable energy output and safe working state under complex terrain.

[0040] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0041] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0042] This embodiment also provides a work path planning device, such as Figure 5 As shown, the work path planning device includes: The planning module 501 is used to obtain the corresponding task of the robot, determine the work range according to the task, and perform path planning for the robot based on the charging point location and the task in the work range to obtain the initial work path. The prediction module 502 is used to obtain the slope sections in the initial operation path and predict the robot's power status in each slope section. The planning module 501 is also used to re-plan the robot's path based on the charging point location and the task in the work area if the robot's power status in any slope section does not match the preset target power status, and to obtain a new initial work path; if the robot's power status in each slope section matches the preset target power status, the initial work path is used as the target work path.

[0043] In some examples, the task includes: at least one work procedure and the work location corresponding to each work procedure; the planning module 501 is also used to generate an initial planning path based on the robot's starting point, ending point and each work location within the work area; predict the expected remaining power of the robot after passing each road segment based on the robot's power consumption requirements for each work procedure and the driving energy consumption of the robot for each road segment in the initial planning path; when the expected remaining power is lower than a preset safety margin, select a charging point from the charging point locations within the work area before that road segment as an intermediate node and insert it into the initial planning path to obtain the initial work path.

[0044] In some examples, the prediction module 502 is also used to calculate the change in the robot's battery level as it passes through each slope segment; based on the change in battery level and the battery level of the robot before entering each slope segment, the prediction module predicts the robot's battery status in the slope segment.

[0045] In some examples, the prediction module 502 is also used to obtain the power difference between the power status and the target power status when the power status is higher than the target power status; compare the power difference with a preset difference threshold; if the power difference is greater than the difference threshold, it is determined that the robot's power status on the sloping road section does not match the preset target power status. In some examples, the prediction module 502 is also used to compare the battery status with a minimum battery threshold when the battery status is less than the target battery status; if the battery status is less than the minimum battery threshold, it is determined that the robot's battery status on the sloping road section does not match the preset target battery status.

[0046] In some examples, the planning module 501 is also used to insert uphill pre-consumption during the path planning process if the robot's power status on any uphill slope segment does not match the pre-set target power status under the replanned initial work path.

[0047] In some examples, the planning module 501 is also used to control the robot to perform tasks according to the target task path.

[0048] According to the technical solution provided in this application embodiment, the operation path planning device obtains the robot's corresponding operation task, determines the operation range based on the task, and performs path planning for the robot based on the charging point locations and the task within the operation range to obtain an initial operation path. It then obtains the slope segments within the initial operation path and predicts the robot's battery status at each slope segment. If the robot's battery status at any slope segment does not match the pre-set target battery status, the device re-plans the robot's path based on the charging point locations and the task within the operation range to obtain a new initial operation path. When the robot's battery status at each slope segment matches the pre-set target battery status, the initial operation path is used as the target operation path. This solution enables the robot to fully consider the impact of slope terrain on energy consumption and energy recovery during the path planning stage, achieving dynamic prediction and adjustment of the robot's battery status. This ensures sufficient power when going uphill and reasonable energy recovery space when going downhill. This avoids the problem in the prior art where the energy consumption characteristics of the robot under different terrain conditions are not fully considered, leading to a planned operation path that cannot match the actual battery changes during operation, thus affecting robot operation.

[0049] Figure 6 This is a schematic diagram of the electronic device 6 provided in an embodiment of this application. Figure 6 As shown, the electronic device 6 of this embodiment includes a processor 601, a memory 602, and a computer program 603 stored in the memory 602 and executable on the processor 601. When the processor 601 executes the computer program 603, it implements the steps in the various method embodiments described above. Alternatively, when the processor 601 executes the computer program 603, it implements the functions of each module / unit in the various device embodiments described above.

[0050] The electronic device 6 can be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The electronic device 6 can include, but is not limited to, a processor 601 and a memory 602. Those skilled in the art can understand that Figure 6 The electronic device 6 is merely an example and is not limited to the electronic device 6, and can include more or fewer components or different components than those shown.

[0051] The processor 601 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like.

[0052] The memory 602 can be an internal storage unit of the electronic device 6, for example, a hard disk or a memory of the electronic device 6. The memory 602 can also be an external storage device of the electronic device 6, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like. The memory 602 can also include both the internal storage unit and the external storage device of the electronic device 6. The memory 602 is used to store computer programs and other programs and data required by the electronic device.

[0053] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0054] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in a computer-readable medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0055] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for planning a work path, characterized in that, The method includes: Obtain the task corresponding to the robot, determine the work area based on the task, and perform path planning for the robot based on the charging point location in the work area and the task to obtain the initial work path; Obtain the slope segments in the initial operation path and predict the battery status of the robot in each slope segment; If the robot's battery status on any of the slope sections does not match the preset target battery status, then the robot's path is replanned based on the charging point locations in the work area and the work task to obtain a new initial work path. If the robot's battery status matches the preset target battery status in each slope section, the initial work path will be used as the target work path.

2. The method according to claim 1, characterized in that, The task includes: at least one work process and a work location corresponding to each work process; based on the charging point locations within the work area and the task, the robot performs path planning to obtain an initial work path, including: An initial planned path is generated based on the robot's starting and ending points, as well as the work locations within the work area; Based on the power consumption requirements of the robot in each work process and the driving energy consumption of the robot in each segment of the initial planned path, the estimated remaining power of the robot after passing through each segment is predicted. When the estimated remaining power is lower than the preset safety margin, a charging point is selected from the charging point locations within the work area before that road segment as an intermediate node and inserted into the initial planned path to obtain the initial work path.

3. The method according to claim 1, characterized in that, Obtain the slope segments in the initial operation path and predict the robot's battery status in each slope segment, including: Calculate the change in the robot's battery level as it traverses each of the aforementioned slope sections; Based on the change in battery power and the battery power of the robot before entering each slope section, the battery status of the robot in the slope section is predicted.

4. The method according to claim 1, characterized in that, The method further includes: When the battery status is higher than the target battery status, the battery difference between the battery status and the target battery status is obtained; The battery power difference is compared with a preset difference threshold. If the battery power difference is greater than the difference threshold, it is determined that the battery power status of the robot on the sloping road section does not match the preset target battery power status.

5. The method according to claim 1, characterized in that, The method further includes: When the battery status is less than the target battery status, the battery status is compared with the minimum battery threshold. If the battery status is less than the minimum battery threshold, it is determined that the robot's battery status on the sloping road section does not match the preset target battery status.

6. The method according to claim 1, characterized in that, After replanning the robot's path based on the charging point locations within the work area and the work task to obtain a new initial work path, the method further includes: If, under the replanned initial work path, the robot's battery status on any uphill slope segment does not match the pre-set target battery status, then uphill pre-consumption is inserted during the path planning process.

7. The method according to claim 1, characterized in that, After using the initial work path as the target work path, the method further includes: controlling the robot to perform work according to the target work path.

8. A work path planning device, characterized in that, The device includes: The planning module is used to obtain the corresponding task of the robot, determine the work range according to the task, and perform path planning for the robot based on the charging point location in the work range and the task to obtain the initial work path. The prediction module is used to obtain the slope sections in the initial operation path and predict the battery status of the robot in each slope section. The planning module is also used to re-plan the path of the robot based on the charging point location in the work area and the work task if the robot's power status in any of the slope sections does not match the preset target power status, so as to obtain a new initial work path; and to use the initial work path as the target work path if the robot's power status in each of the slope sections matches the preset target power status.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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