Path planning method and system for mobile robot, and computer program product

Abstract

The present application provides a path planning method and system for a mobile robot, and a computer program product. The path planning method comprises: obtaining a first region meeting a first preset condition; adjusting or maintaining the first region to obtain a second region; planning a working path in the second region, wherein the working path extends beyond the boundary of the first region, so that when moving along the working path, the mobile robot can move outside the first region to perform positioning calibration. Thus, when moving along the working path, the mobile robot can move to a region with stronger positioning signals outside the first region to perform accurate positioning, thereby ensuring precise movement of the mobile robot.

Description

Mobile robot path planning method and system, and computer program product Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a path planning method and system for a mobile robot, and a computer program product. Background Art

[0002] With the advancement of technology and people's increasing demands for a better quality of life, mobile robots are gradually becoming part of our daily lives and work, such as indoor sweeping robots, outdoor gardening robots, and factory handling robots. Mobile robots move autonomously within their work areas and automatically perform tasks. After the user sets a work area or the mobile robot automatically identifies the work area, it automatically creates a map of the work area and plans a travel path based on the task on the map. It then moves autonomously within the work area according to the planned travel path.

[0003] In the existing technology, for mobile robots that use RTK technology (real-time dynamic differential positioning technology) for positioning, when the working area is blocked by obstacles, or there are severe weather conditions, or there are interference factors, the signal quality of the satellite signal will decrease, resulting in the mobile robot being unable to receive effective satellite positioning signals and thus unable to provide reliable positioning and navigation services. Summary of the Invention

[0004] Based on this, it is necessary to provide a path planning method and system for a mobile robot, and a computer program product to address the above technical problems, which can plan accurate paths in areas with weak positioning signals, thereby controlling the mobile robot to move accurately according to the planned path in areas with weak positioning signals.

[0005] In the first aspect, the present application provides a path planning method for a mobile robot, the method comprising: obtaining a first area that meets a first preset condition; adjusting or maintaining the first area to obtain a second area; planning a working path for the second area, wherein the working path exceeds the boundary of the first area so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

[0006] In the second aspect, the present application also provides a path planning system for a mobile robot, the system comprising: an acquisition module for acquiring a first area that meets a first preset condition; an adjustment module for adjusting or maintaining the first area to obtain a second area; and a planning module for planning a working path for the second area, wherein the working path exceeds the boundary of the first area so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

[0007] In a third aspect, the present application also provides a computer program product, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned path planning method.

[0008] The above introduces a path planning method, system, and computer program product for a mobile robot. The path planning method includes: obtaining a first area that meets a first preset condition; adjusting or maintaining the first area to obtain a second area; planning a working path for the second area, wherein the working path exceeds the boundary of the first area so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

[0009] If there is a first area that meets the first preset condition, such as a first area that meets the condition of weak positioning signal, the movement of the mobile robot in the first area will not be able to ensure accurate positioning. Therefore, the present application actively obtains the first area, adjusts or maintains the first area to obtain the second area, and further performs path planning for the second area, so that the planned working path exceeds the first area where accurate positioning cannot be ensured, so that the mobile robot can move to an area with a stronger positioning signal outside the first area for accurate positioning when moving according to the working path, thereby ensuring the accurate movement of the mobile robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] FIG1 is a flow chart of a path planning method for a mobile robot provided in an embodiment of the present application;

[0011] FIG2 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0012] FIG3 is a schematic diagram of the signal strength distribution of the working area in the historical map;

[0013] FIG4 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0014] FIG5 and FIG6 are schematic structural diagrams of two methods for adjusting the first area provided in the application embodiment;

[0015] FIG7 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0016] 8 and 9 are schematic structural diagrams of another method for adjusting the first area provided in an embodiment of the application;

[0017] 10 and 11 are schematic structural diagrams of another method for adjusting the first area provided in an embodiment of the application;

[0018] FIG12 is a schematic structural diagram of another method for adjusting the first area provided in an embodiment of the application;

[0019] 13 and 14 are schematic structural diagrams of a method for processing the second area provided in an embodiment of the application;

[0020] FIG15 is a schematic structural diagram of another method for processing the second area provided in an embodiment of the application;

[0021] FIG16 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0022] FIG17 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0023] FIG18 and FIG19 are schematic diagrams of a scenario of work path planning provided by an embodiment of the present application;

[0024] FIG20 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0025] FIG21 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0026] FIG22 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0027] FIG23 is a schematic diagram of a scenario for setting path nodes and target nodes provided in an embodiment of the present application;

[0028] FIG24 is a schematic diagram of another scenario of work path planning provided by an embodiment of the present application;

[0029] FIG25 is a schematic diagram of another scenario for setting path nodes and target nodes provided in an embodiment of the present application;

[0030] FIG26 is a schematic diagram of another work path planning scenario provided by an embodiment of the present application;

[0031] FIG27 is a flow chart of another path planning method for a mobile robot provided in an embodiment of the present application;

[0032] FIG28 is a schematic structural diagram of a path planning system for a mobile robot provided in an embodiment of the present application;

[0033] FIG29 is a block diagram of the basic structure of the computer device of this embodiment. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0035] When operating, a mobile robot needs to autonomously move within a work area and perform the corresponding task. Accurate positioning is required during this movement to ensure the robot follows a pre-set path. Typically, the mobile robot is controlled to traverse the work area. A positioning module identifies the work area during movement, or the user manually sets the work area. The mobile robot stores this work area to create a map of the work area and plans a work path on this map based on the task. This path is known as the original work path. Finally, the mobile robot moves along this planned original work path to complete the task.

[0036] However, as mentioned in the background, some positioning modules of the mobile robot may have errors due to various reasons, making it impossible for the mobile robot to obtain reliable positioning and navigation services, and thus unable to complete the corresponding task.

[0037] For example, a garden robot used for outdoor operations is equipped with a first positioning module based on a satellite positioning system and a second positioning module based on vision. The satellite positioning system can be one or more of the Global Positioning System (GPS), Beidou Satellite Navigation System, Galileo Satellite Navigation System, or GLONASS Satellite Navigation Satellite System. The first positioning module primarily utilizes RTK technology (real-time dynamic differential positioning) for positioning. RTK technology achieves precise positioning of the robot by receiving signals from satellites and using the principle of differential positioning. The first positioning module of the garden robot includes components such as a satellite receiving antenna, an RTK module, a 4G module, a Wi-Fi module, a Bluetooth module, and a LoRa module. The satellite receiving antenna is responsible for receiving signals from satellites such as GPS, Beidou, and Galileo; the RTK module uses dual-frequency RTK technology to achieve high-precision measurement of the robot's position; the 4G module, Wi-Fi module, and LoRa module are responsible for data transmission and communication; and the Bluetooth module allows users to configure and control the robot using devices such as mobile phones.

[0038] During the operation of a garden robot, the surrounding operating environment may be complex and changeable. For example, sometimes it is in an open area with no obstructions, good weather conditions and no interference factors, and sometimes it is in an area blocked by obstacles, or with severe weather conditions or interference factors. For open areas with no obstructions, good weather conditions and no interference factors, the satellite positioning signal is usually relatively stable. However, for areas blocked by obstacles, or with severe weather conditions or interference factors, the presence of these factors will cause the quality of the satellite positioning signal in the area to be poor. At this time, if the position information is determined based on the acquired satellite positioning signal, it will lead to inaccurate positioning. Furthermore, if the operation is performed based on inaccurate position information, the garden robot may not be able to effectively complete the work tasks assigned by the user because it deviates from the operating area or operating path.

[0039] Therefore, when satellite signal quality is poor, the first positioning module cannot effectively locate the robot. At this point, the garden robot system must automatically switch to the second positioning module for positioning before continuing operations. Once the satellite signal quality recovers, the garden robot system automatically switches back to using the first positioning module for positioning. Because the second positioning module's positioning accuracy is lower than that of the first, and because the garden robot experiences cumulative errors while using the second positioning module for navigation, it cannot rely on the second positioning module for extended periods of time. Therefore, the positioning data generated by the second positioning module must be calibrated after a certain distance or time interval.

[0040] The embodiments of the present application provide a path planning method for a mobile robot to solve the above-mentioned problem of inaccurate positioning.

[0041] Please refer to Figure 1, which is a flow chart of a path planning method for a mobile robot provided in an embodiment of the present application. As shown in Figure 1, the path planning method may include the following steps:

[0042] Step S1: Acquire a first area that meets a first preset condition.

[0043] As previously mentioned, the mobile robot determines the size of its work area by traversing it or manually setting it by the user, and then creates a map based on the size of the work area. As the mobile robot traverses the work area, or as the user manually sets it, it further identifies information about satellite positioning signals (such as size and quality) at various locations within the work area. This positioning signal and the size of the work area are stored simultaneously to create a map, serving as a historical map that provides a positioning reference for the mobile robot's next operation.

[0044] In some embodiments, before a mobile robot begins operation, it needs to obtain a historical map. It then divides the work area into multiple sub-areas, each of which serves as the original work area. It then plans a work path within the sub-areas, which serves as the original work path. Furthermore, it also obtains positioning signal information from various locations within the work area from the historical map.

[0045] For example, for a lawn mower robot that performs positioning based on the first positioning module, obtaining the intensity distribution of satellite positioning signals in the working area from the historical map (see FIG. 2 ) may specifically include the following steps:

[0046] Step S11: Retrieve a historical map from the robot mower's app. The historical map includes the distribution of satellite positioning signals at each location on the map.

[0047] The historical map may be a grid map, which includes satellite signal distribution of each grid on the map. Please refer to the schematic diagram of signal strength distribution of the working area in the historical map shown in FIG3 .

[0048] Step S12: Preprocessing the satellite positioning signal distribution information.

[0049] After collecting the satellite positioning signal distribution information of each location on the historical map, the satellite positioning signal distribution information is preprocessed, which may include data cleaning, denoising, filtering, etc., to ensure the accuracy and reliability of the satellite positioning signal distribution information.

[0050] Step S13: extracting characteristic information related to the satellite positioning signal strength from the pre-processed satellite positioning signal distribution information.

[0051] Because the acquired satellite positioning signal distribution information is overall positioning information, this step only obtains features related to satellite positioning signal strength, such as average signal strength, maximum signal strength, signal fluctuation, minimum signal strength, etc. Based on this feature information related to satellite positioning signal strength, the positioning signal strength at various locations in the working area can be derived.

[0052] A machine learning model can be trained using the technical solutions of steps S11 and S13 above, and subsequently the machine learning model can be used to obtain characteristic information related to the satellite positioning signal strength. Specifically, historical map data can be input into the machine learning model, and the characteristic information related to the satellite positioning signal strength obtained in step S13 above can be used as the standard result of the machine learning model to verify the output of the machine learning model. By continuously acquiring new map data and characteristic information related to the satellite positioning signal strength, the machine learning model is continuously verified so that the machine learning model is trained. The trained machine learning model is then used to predict the new map data and generate a satellite signal strength distribution map for each location. It should be understood that in actual applications, the machine learning model can also be continuously optimized and updated according to actual needs to improve the accuracy and adaptability of the prediction.

[0053] The method described above can be used to obtain the strength of the positioning signal at each location from the historical map. This step further obtains a first area that meets the first preset condition. The first preset condition may include: the strength of the positioning signal in the area is less than the preset strength value (such as: the carrier-to-noise ratio CN0 of the positioning signal is less than 35dB), and the size of the area is greater than the preset area value. In other words, when the positioning signal in the area is weak, the mobile robot cannot accurately locate in the area, affecting the accuracy of the positioning of the mobile robot. Furthermore, if the area of ​​the area is large, it will have a more serious impact on the positioning of the mobile robot, not only affecting the efficiency of the movement and operation of the mobile robot, but also causing the mobile robot to move to a dangerous area, thereby affecting the safety of the mobile robot. Therefore, this step will obtain an area that meets the first preset condition and define it as the first area. The path planning for the first area is re-performed so that the mobile robot can accurately locate.

[0054] In a specific example, for a grid map representing a working area, the positioning signal strength of each grid can be compared with a preset strength value. If the signal strength of multiple adjacent grids is less than the preset strength value, the grids can be combined. The size of the combined grids is further determined based on the size and number of grids. For example, if the number of combined grids is 20 and the size of each grid is 0.5m*0.5m, the total area of ​​the combined grids is 5m 2 , if the area preset value is 1m 2 , then the area of ​​the combined grids is greater than the preset area value, and the area formed by combining these grids is set as the first area.

[0055] Step S2: adjusting or maintaining the first region to obtain a second region.

[0056] This step mainly refers to adjusting or maintaining the boundary of the first region. The specific scheme will be detailed below. For the sake of convenience, whether the first region is adjusted to form a new region or the first region remains unchanged in this step, it is referred to as the second region.

[0057] Step S3: Planning a working path for the second area, wherein the working path exceeds the boundary of the first area, so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

[0058] Because the positioning signal is weak in the second area, this step replans the working path in that area. This replanned working path differs from the original working path and is designed based on the characteristics of the second area. Furthermore, the planned working path extends beyond the boundary of the first area, where the positioning signal is weak. In other words, a portion of the working path lies outside the first area. As a result, while moving along the working path, the mobile robot can relocate to locations outside the first area where the positioning signal is stronger, thereby improving positioning accuracy.

[0059] Therefore, this embodiment actively acquires a first area with a weak positioning signal and a larger area size, adjusts or maintains the first area to obtain a second area, and further performs path planning on the second area so that the planned working path exceeds the first area where accurate positioning cannot be ensured, so that the mobile robot can move to an area with a stronger positioning signal outside the first area for accurate positioning when moving according to the working path, thereby ensuring the accurate movement of the mobile robot.

[0060] Please refer to Figure 4, which is a flow chart of another mobile robot path planning method provided by an embodiment of the present application. As shown in Figure 4, this embodiment mainly introduces a method for adjusting the first area, which specifically includes the following steps:

[0061] Step S41: Obtain the size, regularity, and / or shape of the first area.

[0062] In the grid map, the size of the first area can be obtained by the number of grids occupied by the first area and the area occupied by each grid.

[0063] Regularity refers to the similarity between the shape rule of the first area and a preset standard shape rule. The standard shape rule may include a circle, an ellipse, a regular polygon (such as a rectangle, a regular hexagon, etc.).

[0064] Regularity can be determined by obtaining actual parameters of the shape of the first region, such as its perimeter, area, curvature, and rectangularity. The actual parameters are compared with pre-set standard parameters of a standard shape. For example, for a square first region, the length of each side of the first region can be calculated and compared with the length of the square's diagonal to assess its regularity. The regularity of the first region is determined based on the differences, where the regularity can be expressed as a percentage or other unit of measure.

[0065] In a specific embodiment, the regularity of the first region can also be identified using a machine learning model. First, multiple test samples of the first region are collected, and the perimeter, area, curvature, rectangularity, etc. of the test samples are obtained. These samples are input into the machine learning model, and the output of the machine learning model is compared with the standard results of the test samples. The parameters of the machine learning model are adjusted based on the comparison results. Through continuous testing and adjustment, a machine learning model that meets the requirements is trained, and the regularity of the first region can be identified using this machine learning model.

[0066] The shape of the first area can be obtained through a visual sensor, that is, an image of the first area is captured by the visual sensor, the image of the first area is analyzed to obtain image information representing the edge of the first area, and the shape contour of the first area is obtained based on the image information of the edge, thereby obtaining the shape of the first area.

[0067] In one specific embodiment, contour tracing techniques can be used to identify and analyze the first region. Contour tracing is a pixel-based shape analysis method that forms closed contours by finding and connecting consecutive pixels in an image. For more complex shape analysis, the Hough transform can be used. The Hough transform converts edges in an image into a representation in parameter space, making it easier to identify and understand shapes. Using the Hough transform, lines, circles, or other basic shapes can be detected in the first region. Once the contour and / or Hough transform are applied, information about the shape of the first region can be extracted from the results.

[0068] In this step, the size, regularity, and shape characteristics of the first region are first obtained, and then the adjustment method of the first region is determined based on these characteristics, so that the adjustment of the first region is simpler and more in line with the operation requirements of the mobile robot.

[0069] Step S42: Determine a method for adjusting the first area based on the size, regularity, and / or shape of the first area.

[0070] In this step, the method for adjusting the first region may be determined based on only one of the characteristics of the first region, namely, size, regularity, and shape, or based on two or three characteristics.

[0071] In one embodiment, the adjustment method of the first area can be determined based on the size of the first area. For example, if the size of the first area is moderate, such as for a lawn mowing robot, if the size of the first area is greater than 5m 2 and less than 25m 2 , the first area can be partially expanded. If the first area is circumscribed into a regular polygon, it can avoid driving too long in areas with good satellite signals, which will affect the mowing efficiency. If the size of the first area is small, such as in a mowing robot, the size of the first area is less than or equal to 5m 2 , the first area can be expanded as a whole, because when the size of the first area is relatively small, the overall expansion of the first area has little effect on the mowing efficiency; if the size of the first area is large, for example, in a mowing robot, the size of the first area is greater than 25m 2 , the working sub-areas where the first area is located can be merged. Because when the area is relatively large, the various working sub-areas where the first area is located can be directly merged, and the merged working sub-areas can be used as the expanded area. This expansion method is simple, can reduce computing power, and improve the response speed of the lawn mowing robot.

[0072] In one embodiment, the adjustment method of the first area can also be determined based on the regularity of the first area. Specifically, if the first area is a regular shape (such as a regular polygon), the first area can be expanded as a whole or partially. This implementation method is simple, can process fewer nodes, and can reduce computing power. If the first area is an irregular shape, the adjustment method of the first area can be further determined based on the size of the first area. For example, if the size of the first area is less than or equal to 5m 2 , the first area can be partially expanded, such as a circumscribed rectangle, etc., which can improve the operating efficiency of the mobile robot in the second area; if the size of the first area is greater than 5m 2 , the working sub-areas where the first area is located can be merged. This expansion method is simple, can reduce computing power, and improve the response speed of the mobile robot to adjust the first area.

[0073] In one embodiment, the adjustment method of the first area can also be determined according to the shape of the first area. For example, if the first area is a polygon, the first area can be partially expanded, such as a circumscribed rectangle. If the first area is a circle, a sector or an ellipse, the first area can be expanded as a whole or partially.

[0074] Methods for adjusting the first area include: expanding the first area as a whole or partially, or merging the working sub-areas where the first area is located. Expanding the first area as a whole means moving the boundaries of the first area outward as a whole. As shown in FIG5 , there are two first areas, one of which is a rectangle and the other is an irregular shape. Both first areas can be expanded as a whole to form a second area. Partially expanding the first area means moving part of the boundaries of the first area outward. As shown in FIG6 , if the first area is an irregular circle, a circumscribed rectangle of the irregular circle is drawn, i.e., part of the boundaries of the first area are moved outward to form a regular rectangle, thereby obtaining the second area. It should be understood that the first area shown in FIG6 can also be expanded to other regular polygons. By expanding the first area as a whole or partially, or merging the working sub-areas where the first area is located, when planning the working path, it is possible to plan outside the first area so that the mobile robot can move outside the first area for positioning and calibration, thereby improving the positioning accuracy of the mobile robot.

[0075] Referring to FIG. 7 , the specific method for merging the working sub-areas where the first area is located includes the following steps:

[0076] Step S71: Acquire the working sub-area where the first area is located.

[0077] As described above, after obtaining the historical map, the working area is divided into multiple working sub-areas, and the working sub-area where the first area is located is obtained. As shown in Figure 8, the first area is located in four working sub-areas, and these four working sub-areas are used as the working sub-areas where the first area is located.

[0078] Step S72: If there are multiple working sub-areas, merge the working sub-areas, or obtain the proportion of the first area in each working sub-area, and determine whether there is a working sub-area whose proportion is less than the first preset value. If so, only merge the first area with the remaining working sub-areas.

[0079] This step includes two merging methods. The first merging method is: merging each of the working sub-areas. As shown in Figures 8 and 9, the first area occupies four working sub-areas, and the four working sub-areas are merged to form the second area. This method is simple and reduces computing power.

[0080] The second merging method is as follows: first, the proportion of the first area in each of the working sub-areas is obtained, and then it is determined whether there is a working sub-area whose proportion is less than a first preset value. If so, the first area is merged with the remaining working sub-areas. In this case, if the working sub-area whose proportion is less than the first preset value is still included, the second area formed after the merger will contain an unnecessary expansion part. Therefore, the first area is directly merged with the remaining working sub-areas, and the working sub-area whose proportion is less than the first preset value is excluded to ensure that the merged area is more accurate and efficient, thereby improving the working efficiency of the mobile robot. For details, please refer to Figures 10 and 11. If the proportion of the first area in the two working sub-areas is less than the first preset value, the first area located in the two working sub-areas is merged with the remaining two working sub-areas. It is worth noting that the first area can also be expanded in the two working sub-areas whose proportion is less than the first preset value so that the boundary of the expanded area is flush with the boundary of the working sub-area part, and then merged with the remaining two working sub-areas. Please refer to Figures 10 and 12 for details. If the proportion of the first area in the two working sub-areas is less than the first preset value, the first area will be expanded outward in the part of the two working sub-areas. As shown in Figure 12, the first area is extended in the up and down directions at the boundaries of the two working sub-areas until it is flush with the boundaries of the working sub-areas, and then merged with the remaining two working sub-areas to form a second area. This method can ensure that the shape of the merged second area is a regular shape, which is convenient for planning the working path.

[0081] It is worth noting that when adjusting the first area, it is necessary to analyze the boundary features of the first area, and then determine the adjustment direction based on the boundary features. Specifically, first analyze the boundary of the first area in detail to determine whether the boundary of the first distinction is smooth, whether there is an inflection point, whether it is clearly separated from the adjacent area, etc. These features can provide clues on how to make adjustments. Then, based on the analyzed boundary features, determine in which directions to expand the area. For example, if the boundary is smooth, consider expanding evenly in all directions; if the boundary has an inflection point, consider expanding at least at the inflection point position to form a regular second area, which facilitates the planning of subsequent work paths.

[0082] Furthermore, during the expansion adjustment process of the first region, the original shape characteristics of the first region should be maintained as much as possible. For example, a certain curvature should be maintained and unnecessary deformation should be avoided. Furthermore, the relationship between the first region and adjacent regions can be analyzed to determine whether a specific relationship or gap with the adjacent region is necessary. For example, if the first region is close to an adjacent region, further expansion can be performed to intersect with the adjacent region. Path planning can then be performed for the two regions as a whole, facilitating continuous work path planning and improving the efficiency of the mobile robot's movement and operation.

[0083] The above embodiment describes how to adjust the first area to form a second area. After the second area is formed, the path planning for the second area is further performed so that the mobile robot can move according to the replanned working path. Before path planning, the characteristics of the second area can be further analyzed and processed to make the processed second area more convenient for path planning. There are two specific solutions:

[0084] The first solution is to first determine whether the second area exceeds the boundary of the working area, where the working area is the boundary of the working area in the historical map, and control the mobile robot to move and operate in the working area within the boundary. If it is determined that the second area exceeds the boundary of the working area, the intersection of the second area and the working area is obtained. As shown in Figures 13 and 14, part of the second area exceeds the boundary of the working area. For example, in Figure 13, the right boundary of the second area exceeds the boundary of the working area and is located outside the working area. If the second area is used for path planning, the mobile robot will move outside the working area, affecting the operating efficiency of the mobile robot. Being outside the working area will increase the unknown dangers encountered by the mobile robot. Therefore, it is necessary to adjust the second area. As shown in Figure 14, the intersection of the second area and the working area is obtained, and the portion of the second area that exceeds the working area is discarded. This prevents the mobile robot from moving outside the working area when moving in the second area, thereby ensuring the operating efficiency and safety of the mobile robot.

[0085] The second solution is to determine whether there is an intersection between adjacent second areas. If there is an intersection, the second areas with the intersection are processed as a union. If there is an intersection between adjacent second areas, it means that the work paths planned in the adjacent second areas partially overlap. If each area is planned separately, the movement efficiency and working efficiency of the mobile robot will be affected. For example, in a lawn mowing robot, if the intersection area is repeatedly mowed, on the one hand, the mowing efficiency will be affected, and on the other hand, the lawn will be continuously crushed and damaged. Therefore, it is necessary to process the two adjacent second areas. This embodiment specifically processes the two adjacent second areas as a union, so that the work paths planned in the merged area do not overlap, thereby improving the working efficiency of the mobile robot. As shown in Figure 15, if there is an intersection between two adjacent second areas, the two second areas are processed as a union and merged into one area.

[0086] After processing the second area, a working path for the second area can be planned. Referring to FIG. 16 , the method for planning the working path for the second area may specifically include the following steps:

[0087] Step S161: Determine whether the second area and the working area have a common boundary.

[0088] The work area is the area within which the mobile robot's operations are restricted. If the second area and the work area share a common boundary, this indicates that the second area is located at the boundary of the mobile robot's operating area. Therefore, when planning the work path for the second area, care must be taken to ensure that the mobile robot does not exceed the boundaries of the work area when moving along the work path to ensure the safety of the mobile robot. Therefore, this step first determines whether the second area and the work area share a common boundary, which serves as a reference for subsequent work path planning.

[0089] There are three methods for determining whether the second area and the working area share a common boundary:

[0090] The first method is to compare the coordinates of the second area and the working area boundary. The boundary coordinates of the second area are compared with the boundary coordinates of the working area one by one. If there are coordinate points that appear on the boundaries of the two areas at the same time, or the two areas overlap at some locations, then it can be considered that the two areas have a common boundary.

[0091] The second method is to use a mathematical algorithm to determine whether two areas intersect or overlap. For example, a point-to-polygon positional relationship algorithm can be used to determine whether a point (representing a point on the boundary) is inside a polygon (representing the working area or the second area).

[0092] The third method is to determine the distance between the boundary of the second area and the boundary of the working area. If the distance is less than a preset distance threshold, it can be considered that they have a "shared boundary." This is because if the boundary of the second area and the boundary of the working area are close, ignoring the boundary of the working area may cause the planned working path to exceed the working area. Therefore, it is necessary to determine that the second area and the working area have a shared boundary.

[0093] In this step, if there is a common boundary, the process jumps to step S162 ; if there is no common boundary, the process jumps to step S163 .

[0094] Step S162: Determine a path planning direction for the second area based on the shared boundary.

[0095] The path planning direction refers to the direction indicated by the working path when planning the working path. As shown in Figure 18, when planning a bow-shaped working path, the direction of the long side of the bow is the path planning direction.

[0096] As mentioned above, if there is a shared boundary, when planning the working path in the second area, it is necessary to consider that the mobile robot cannot exceed this shared boundary when moving along the working path to ensure that it does not exceed the working area. Therefore, the path planning direction of the second area needs to be determined based on this shared boundary.

[0097] Specifically, referring to FIG. 17 , the following steps may be included:

[0098] Step S171: Obtain the number of the shared boundaries.

[0099] Step S172: Determine the path planning direction according to the number of the shared boundaries.

[0100] If there is only one shared boundary, the direction that does not cross the shared boundary will be used as the path planning direction. As shown in Figure 18, there is a shared boundary between the bottom of the second area and the working area, and the path planning direction does not cross the shared boundary. For example, as shown in Figure 18, the path planning direction is parallel to the shared boundary. In the path planning direction, when the mobile robot moves to the end of the working path, a portion of the mobile robot's body will exceed the second area. Since the exceeded portion is still within the working area, it does not affect the safety of the mobile robot. In the direction that crosses the shared boundary, the planned working path does not exceed the working area, and the mobile robot is parallel to the shared boundary when moving along the working path. In this way, the mobile robot can be controlled not to exceed the shared boundary, that is, the mobile robot is controlled to move within the working area, ensuring the safety of the mobile robot.

[0101] If there is more than one shared boundary, the direction of the shared boundary with obstacles or dangerous areas is used as the path planning direction. Because the working path needs to traverse the entire working area from top to bottom and left to right when setting the working path, when there is more than one shared boundary, no matter how the path planning direction is set, there will be a situation where the mobile robot exceeds the working area when moving along part of the working path. Therefore, this embodiment selects the direction of the shared boundary with obstacles or dangerous areas as the path planning direction, that is, the path planning direction is parallel to the shared boundary with obstacles or dangerous areas. As a result, the mobile robot will exceed the working area when moving along the working path parallel to the path planning direction, because there are no obstacles or dangerous areas in this part of the area, so the mobile robot is safe when moving in this part of the area. As shown in Figure 19, the bottom boundary and the right boundary of the second area both share a shared boundary with the working area, and there is an obstacle outside the working area at the bottom. In this way, the direction of the shared boundary at the bottom is used as the path planning direction, and the working path is planned along the direction parallel to the shared boundary at the bottom. When the mobile robot moves along the working path, it will exceed the common boundary on the right side, that is, it will exceed the working area on the right side. Because this part of the area is safe, the safety of the mobile robot can be guaranteed. In addition, the mobile robot does not exceed the working area when moving on the working path at the bottom, so the risk of the mobile robot moving to the outside and colliding with obstacles can be avoided.

[0102] Step S163: determining a path planning direction based on the overall working direction of the working area, or determining a path planning direction based on the size of the second area.

[0103] In this step, the path planning direction is determined based on the overall working direction of the work area. Since the overall working direction has been preset in advance, this solution is simple and convenient, and can reduce computing power and costs.

[0104] In addition, a specific solution for determining the path planning direction based on the size of the second area can be found in FIG. 20 , which specifically includes the following steps:

[0105] Step S201: Obtain the long side direction or the short side direction of the second area.

[0106] The long side and short side of the second area are obtained according to the size of the second area. In this step, the image of the second area can be recognized by a visual sensor, and then the long side and short side of the second area can be analyzed from the image.

[0107] Step S202: using the long side direction or the short side direction as the path planning direction.

[0108] The determination of whether to use the long side or short side direction is mainly based on the length values ​​of the long side and the short side. If the value of the short side meets the first length threshold, for example, it is greater than two fuselage lengths and less than ten fuselage lengths, the direction of path planning can be determined according to the short side direction. This ensures that the mobile robot can move a certain distance and perform a certain distance of work when moving on the short side, and can also perform a positioning calibration in a short time, which can improve positioning accuracy. If the value of the long side meets the second length threshold, for example, it is greater than 10 fuselage lengths but less than 50 fuselage lengths, the direction of path planning is determined according to the long side direction. This can improve work efficiency and also avoid positioning errors caused by not performing positioning calibration for a long time.

[0109] Since the first area of ​​the present application is an area with a weak positioning signal, positioning in this area is usually performed by the second positioning module of the mobile robot. For example, for a lawn mowing robot, it can be positioned by the first positioning module in an area with a strong positioning signal, but can be positioned by the second positioning module within the first area. That is, positioning can be performed by the second positioning module within the first area, and when moving outside the first area, it can be switched to precise positioning by the first positioning module. When the second positioning module is performing positioning, it is greatly affected by the environment. In dark or bright light, or other interference environments, the second positioning module cannot obtain accurate environmental information, so the positioning accuracy is seriously reduced. Therefore, in the scheme of selecting the short side or the long side as the path planning direction, it is necessary to further determine it in combination with the environmental quality of the second area. Specifically, referring to Figure 21, the following steps may be included:

[0110] Step S210: Acquire the environmental quality of the second area.

[0111] Environmental quality refers to factors that affect the image acquisition of visual sensors, such as light intensity, the size of obstructions, and the presence of haze.

[0112] Step S211: Determine whether the environmental quality of the second area meets a second preset condition.

[0113] The second preset condition refers to the condition under which the visual sensor can obtain a clear image, which can be specifically set according to different visual sensors, such as whether there is a suitable light intensity, whether there are no obstructions or there are few obstructions, whether the weather is clear, etc.

[0114] If the environmental quality of the second area meets the second preset condition, the process jumps to step S212 ; if the environmental quality of the second area does not meet the second preset condition, the process jumps to step S213 .

[0115] Step S212: taking the long side direction as the path planning direction.

[0116] If the environmental quality of the second area meets the second preset condition, it means that the ambient light is suitable and there are no obstructions or other interference environments. In this way, the mobile robot will produce a large cumulative positioning error only after traveling a long distance. Therefore, the mobile robot can use satellite signals to perform positioning calibration outside the first area after traveling a long working path. At this time, the long side direction needs to be used as the path planning direction.

[0117] Step S213: taking the short side direction as the path planning direction.

[0118] The environmental quality of the second area does not meet the second preset condition. For example, in dark or bright environments, or when there are obstructions and other interference environments, the visual sensor cannot obtain a clear image, so the positioning accuracy is seriously reduced. In this way, the mobile robot will produce a large cumulative positioning error after traveling a short distance. Therefore, if it needs to travel a shorter distance, it must move outside the first area to use satellite signals for positioning calibration. At this time, the short side direction needs to be used as the path planning direction.

[0119] The above describes that when the first area is adjusted to form the second area, the path planning direction when planning the working area of ​​the second area is first determined. After determining the path planning direction, the working path planning can be performed based on the path planning direction. The planning of the working path can be carried out according to the size of the fuselage. For example, when planning the bow-shaped working path, the working path is set along the path planning direction, and the two ends of the working path intersect with the boundary of the second area, as shown in Figures 18 and 19. Since the second area formed by the adjustment belongs to the expansion of the first area, the positioning signal at the boundary position of the second area is a satellite signal that can be normally positioned. When the mobile robot moves along the working path to the boundary of the second area, it can be accurately positioned by the first positioning module, such as the first positioning module.

[0120] However, the positioning signals at the boundary and within the boundary of the second area obtained while maintaining the first area are weak, making accurate positioning impossible. Therefore, when the first area is maintained and the second area is formed, it is necessary to set part of the working path outside the second area to control the mobile robot to move to the area with stronger positioning signals outside for accurate positioning. For details, please refer to Figure 22, which includes the following steps:

[0121] Step S220: While maintaining the first area, obtain the path nodes on the boundary of the second area.

[0122] Specifically, this step first obtains the boundary of the second region. Then, based on the boundary of the second region, a circumscribed figure is drawn for the second region. For example, a circumscribed rectangle of the first region, a circumscribed circle of the second region, a circumscribed regular hexagon, etc. can be drawn. The circumscribed figure is then meshed, and the intersection of the resulting mesh and the boundary of the second region is the path node. As shown in Figure 23, the second region is an irregular circle. First, a circumscribed rectangle of the second region is drawn, and then the circumscribed rectangle is meshed. The intersection of the resulting mesh and the boundary of the second region is the path node.

[0123] Step S221: adjusting the path nodes according to a preset rule to generate a target node, wherein the target node is located outside the second area.

[0124] Specifically, the path nodes can be adjusted along the planned path direction to a predetermined distance from the boundary of the second area, such as the distance of one mobile robot body. As shown in FIG23 , if the planned path direction is from left to right, the path nodes on the left and right sides are adjusted to a predetermined distance outside the boundary of the second area, such as the distance of one mobile robot body.

[0125] In one embodiment, only the path nodes at both ends of a working path can be obtained, and then the path nodes at both ends are adjusted by a preset distance outside the second area at the same time to obtain the target nodes at both ends, and the target nodes at both ends are used as the length value of the working path. The distance between the target nodes at both ends must be no less than the side length of the circumscribed figure in the same direction, to ensure that when the target nodes at both ends are used as the length value of the working path, both ends of all working paths are located outside the second area, so as to provide accurate positioning for the mobile robot. For example, Figure 23 obtains the target nodes at the left and right ends of a straight line parallel to the path planning direction. And the distance between the target nodes needs to be no less than the length of the side length of the circumscribed rectangle in the path planning direction.

[0126] In another embodiment, the path nodes can be adjusted along the path planning direction so that the connection lines of the path nodes meet the preset shape. Specifically, the outermost path node can be obtained, and the target node based on the path node is adjusted, and the path nodes at other positions are all moved to the outside of the second area to obtain the target node, so that each target node is connected to form a rectangle to facilitate planning the work path. As shown in Figure 25, the outermost path nodes on the left and right sides can be obtained as the target nodes of the benchmark, and the path nodes at other positions are adjusted to be flush with the target nodes of the benchmark, and then all the target nodes are connected to obtain a rectangular shape, and this shape is exactly the circumscribed rectangle of the second area. Planning the work path within the area of ​​this rectangle is convenient and simple.

[0127] Step S222: planning a working path of the second area based on the target node.

[0128] Please refer to Figure 24 for details. Connect each target node end to end in sequence to plan the working path.

[0129] Since the target node is located outside the second area, at least part of the working path planned according to the target node is located outside the second area. When the mobile robot moves along the working path, it can move to an area outside the second area where the positioning signal is stronger for accurate positioning, thereby improving the positioning accuracy of the mobile robot.

[0130] Among them, when planning the working path of the second area according to the target node, the danger of the target node can also be judged. Specifically, it can be first judged whether the target node is in the dangerous area. If the target node is in the dangerous area, the target node is adjusted to outside the dangerous area. In a specific embodiment, the position of the target node can be adjusted to a position closer to the boundary of the second area along the path planning direction. As shown in Figure 26, there is a target node located at an obstacle. If the target node is not adjusted, the working path planned according to the target node will pass through the obstacle, posing a safety threat to the mobile robot. Therefore, it is necessary to adjust the target node outside the obstacle, specifically to a position closer to the boundary of the second area.

[0131] After planning the working path of the second area, the mobile robot can move along the planned working path. Since the second area is formed without adjusting the first area, it is necessary to control the time when the mobile robot moves in the second area. Please refer to Figure 27. Specifically, the following steps may be included:

[0132] Step S2701: Control the mobile robot to work according to the working path.

[0133] As mentioned above, the working path of this embodiment is formed when the first area is not adjusted.

[0134] Step S2702: Obtain the working time of the mobile robot in the second area.

[0135] Since the positioning signal in the second area cannot be used for accurate positioning, the time for the mobile robot to move in the second area needs to be strictly controlled. Therefore, the working time of the mobile robot in the second area needs to be obtained first.

[0136] Step S2703: If the working time exceeds the preset time, control the mobile robot to move outside the second area to perform posture calibration.

[0137] In this step, a time threshold can be set. If the mobile robot is still moving in the second area when the time threshold is reached, it means that the positioning of the mobile robot has seriously deviated. In this case, it is necessary to control the mobile robot at the current position to move outside the second area for posture calibration to achieve accurate positioning of the mobile robot, quickly complete the operation in the second area, and improve the robot's work efficiency.

[0138] The present application also provides a mobile robot path planning system, which is applied to the path planning method described above. Specifically, please refer to FIG. 28 , which is a schematic diagram of the structure of the mobile robot path planning system provided by the present application. As shown in FIG. 28 , the system 70 includes:

[0139] Acquisition module 71 is configured to acquire a first area that meets a first preset condition. The first preset condition may include: the positioning signal strength of the area is less than a preset strength value (e.g., the carrier-to-noise ratio (CN0) of the positioning signal is less than 35 dB), and the area size is greater than a preset area value. Specifically, the first area is an area with a weak positioning signal and a size greater than the preset area value. The specific acquisition method is as described above and will not be repeated here.

[0140] The adjustment module 72 is configured to adjust or maintain the first region to obtain a second region. Specifically, the adjustment module 72 may analyze regional characteristics of the first region, such as size, regularity, and shape, to determine whether to adjust or maintain the first region. The specific solution is as described above and will not be repeated here.

[0141] The planning module 73 is used to plan the working path of the second area, wherein the working path exceeds the boundary of the first area, so that the mobile robot can move to the outside of the first area for positioning calibration when moving along the working path. Because the positioning signal is weak in the second area, the planning module 73 re-plans the working path of the area. The re-planned working path and the original working path may be different, and it can be planned according to the characteristics of the second area. And the planned working path exceeds the boundary of the first area where the positioning signal is weak, that is, a part of the working path is located outside the first area. Therefore, when the mobile robot moves along the working path, it can move to a position outside the first area where the positioning signal is strong for accurate positioning, thereby improving the accuracy of positioning. The specific planning method of the working path of the second area is as described above and will not be repeated here.

[0142] To solve the above technical problems, the present application also provides a computer device. Specific reference is made to FIG29 , which is a basic structural block diagram of the computer device of the present embodiment.

[0143] The computer device 6 includes a memory 61, a processor 62, and a network interface 63 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 6 with components 61-63, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0144] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0145] The memory 61 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk, optical disk, etc. In some embodiments, the memory 61 can be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 can also be an external storage device of the computer device 6, such as a plug-in hard disk equipped on the computer device 6, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 61 can also include both the internal storage unit of the computer device 6 and its external storage device. In this embodiment, the memory 61 is generally used to store the operating system installed on the computer device 6 and various information management operating systems, such as computer-readable instructions for the path planning method of the mobile robot. In addition, the memory 61 can also be used to temporarily store various types of data that have been output or are to be output.

[0146] In some embodiments, the processor 62 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 62 is generally used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is used to execute computer-readable instructions or process data stored in the memory 61, such as computer-readable instructions for executing a path planning method for a mobile robot.

[0147] The network interface 63 may include a wireless network interface or a wired network interface. The network interface 63 is generally used to establish a communication connection between the computer device 6 and other electronic devices.

[0148] The present application also provides another embodiment, namely, providing a computer program product, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the path planning method for a mobile robot as described above.

[0149] The present application provides a path planning method and system for a mobile robot. The path planning method includes: obtaining a first area that meets a first preset condition; adjusting or maintaining the first area to obtain a second area; planning a working path for the second area, wherein the working path exceeds the boundary of the first area so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

[0150] If there is a first area that meets the first preset condition, such as a first area that meets the condition of weak positioning signal, the movement of the mobile robot in the first area will not be able to ensure accurate positioning. Therefore, the present application actively obtains the first area, adjusts or maintains the first area to obtain the second area, and further performs path planning for the second area, so that the planned working path exceeds the first area where accurate positioning cannot be ensured, so that the mobile robot can move to an area with a stronger positioning signal outside the first area for accurate positioning when moving according to the working path, thereby ensuring the accurate movement of the mobile robot.

[0151] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0152] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0153] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A path planning method for a mobile robot, wherein: The method comprises: Acquire a first area that meets a first preset condition; adjusting or maintaining the first area to obtain a second area; Planning a working path for the second area, wherein the working path exceeds a boundary of the first area, so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

2. The path planning method according to claim 1, wherein: Before adjusting the first area, the method further includes: Obtaining the size, regularity, or shape of the first region; A manner of adjusting the first region is determined based on the size, or / and regularity, or / and shape of the first region.

3. The path planning method according to claim 1, wherein: The method for adjusting the first area further includes: Expanding the first area entirely or partially; Alternatively, the working sub-areas where the first area is located are merged.

4. The path planning method according to claim 3, wherein: The method of merging the working sub-areas where the first area is located further includes: Acquire the working sub-area where the first area is located; Merging the various working sub-areas; Alternatively, the proportion of the first area in each working sub-area is obtained, and it is determined whether there is a working sub-area whose proportion is less than a first preset value. If so, only the first area is merged with the remaining working sub-areas.

5. The path planning method according to claim 1, wherein: Before planning the working path of the second area, the method further includes: determining whether the second area exceeds a boundary of the working area; If yes, obtain the intersection of the second area and the working area.

6. The path planning method according to claim 1, wherein: Before planning the working path of the second area, the method further includes: Determining whether there is an intersection between adjacent second areas; If there is an intersection, the second areas with the intersection are subjected to a union process.

7. The path planning method according to claim 1, wherein: The method for planning a working path for the second area further includes: Determining whether the second area and the working area have a common boundary; If yes, determining a path planning direction for the second area based on the shared boundary; If not, the path planning direction is determined based on the overall working direction of the working area, or the path planning direction is determined based on the size of the second area.

8. The path planning method according to claim 7, wherein: The method for determining the path planning direction of the second area based on the shared boundary further includes: Obtaining the number of the common boundaries; The path planning direction is determined according to the number of the shared boundaries.

9. The path planning method according to claim 8, wherein: The method for determining the path planning direction according to the number of the shared boundaries further includes: If there is only one common boundary, the direction that does not pass through the common boundary is used as the path planning direction; If there is more than one common boundary, the direction of the common boundary with obstacles or dangerous areas is used as the path planning direction.

10. The path planning method according to claim 7, wherein: The method for determining the path planning direction based on the size of the second area further includes: Obtaining the long side direction or the short side direction of the second area; The long side direction or the short side direction is used as the path planning direction.

11. The path planning method according to claim 10, wherein: The method of using the long side direction or the short side direction as the path planning direction further includes: obtaining the environmental quality of the second area; Determining whether the environmental quality of the second area meets a second preset condition; If yes, take the long side direction as the path planning direction; If not, the short side direction is used as the path planning direction.

12. The path planning method according to claim 1, wherein: The method for planning a working path for the second area includes: While maintaining the first area, obtaining path nodes on the boundary of the second area; Adjusting the path nodes according to a preset rule to generate a target node, wherein the target node is located outside the second area; A working path for the second area is planned based on the target node.

13. The path planning method according to claim 12, wherein: The method for adjusting the path nodes according to preset rules includes: Along the planned path direction, the path node is adjusted to a preset distance from the boundary of the second area.

14. The path planning method according to claim 12, wherein: The method for adjusting the path nodes according to a preset rule further includes: Along the planned path direction, the path nodes are adjusted so that the connection lines of the path nodes meet the preset shape.

15. The path planning method according to claim 12, wherein: Before planning a working path for the second area based on the target node, the method includes: Determining whether the target node is in a dangerous area; If the target node is in the dangerous area, the target node is adjusted to outside the dangerous area.

16. The path planning method according to claim 15, wherein: The method of adjusting the target node to outside the dangerous area includes: Along the planned path direction, the position of the target node is adjusted to a position closer to the boundary of the second area.

17. The path planning method according to claim 1, wherein: After planning the working path of the second area, the method further includes: Controlling the mobile robot to work according to the working path; Obtaining a working time of the mobile robot in the second area; If the working time exceeds a preset time, the mobile robot is controlled to move outside the second area to perform posture calibration.

18. A path planning system for a mobile robot, wherein: The system comprises: An acquisition module, configured to acquire a first area that meets a first preset condition; an adjusting module, configured to adjust or maintain the first area to obtain a second area; A planning module is used to plan a working path of the second area, wherein the working path exceeds the boundary of the first area, so that the mobile robot can move outside the first area for positioning calibration when moving along the working path.

19. A computer program product, wherein The computer program product stores computer-readable instructions, which can be executed by at least one processor to enable the at least one processor to perform the steps of the path planning method according to claim 1.

Images