A bowing motion guidance method

Abstract

This application discloses a bow sweeping motion guidance method, relating to the technical field of smart home appliances. This method is applied to robots and includes: determining a target bow sweeping path based on the outer contour features in a map corresponding to the current working environment; the target bow sweeping path includes at least one bow sweeping branch; determining the next optimal bow sweeping branch to be cleaned based on the robot's real-time position, the position information of each bow sweeping branch, and cleaning information; and generating an optimal connection path to the starting position of the optimal bow sweeping branch based on the position information and real-time position of the optimal bow sweeping branch. Therefore, this application has the advantages of neat and orderly robot cleaning work and improved work efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent household appliances, in particular to a bow-sweep motion guiding method. BACKGROUND

[0002] A sweeping and mopping robot is a cleaning robot that can replace manual work to complete basic household floor cleaning. The main motion mode of the sweeping and mopping robot when performing cleaning work is to move in a bow-shaped path and clean synchronously. In the prior art, the cleaning robot needs to work independently when performing a cleaning task, but due to the limited size of most cleaning robots, the mobile power source that can be carried by the robot itself cannot be too large, and the battery power supporting the robot to perform cleaning work is also limited. After leaving the factory, there are certain differences between the working environments of each robot, for example, the outer contour shapes of the working environments are different, the working environments have obstacles, and the number, position or size of the obstacles are also different. The cleaning robot is likely to waste the available cleaning time during the bow-sweep motion due to unreasonable navigation path setting or obstacle blocking, thereby causing the problem of insufficient power and forced interruption of cleaning work when the cleaning work is not completed. SUMMARY

[0003] The purpose of the present application is to provide a bow-sweep motion guiding method. The robot generates a suitable bow-sweep path and determines the next bow-sweep branch to be cleaned and the connection path based on the outer contour features of the environment and the real-time position of the robot, thereby effectively improving the work efficiency and work quality of the robot, making the cleaning work of the robot more orderly and clean, effectively saving power, and providing users with a good user experience.

[0004] Embodiments of the present application are implemented as follows:

[0005] The first aspect of the embodiment of the present application provides a bow-sweep motion guiding method. The method is applied to a robot, and the method comprises: determining a target bow-sweep path according to the outer contour features in a map corresponding to a current working environment; the target bow-sweep path comprises at least one bow-sweep branch; determining an optimal bow-sweep branch to be cleaned next based on the real-time position of the robot, the position information and cleaning information of each bow-sweep branch; and generating an optimal connection path to the starting position of the optimal bow-sweep branch based on the position information of the optimal bow-sweep branch and the real-time position.

[0006] In an embodiment, before determining the target arch sweeping path according to the contour feature in the map corresponding to the current working environment, the method further comprises: controlling the robot to move a preset angle along the contour wall of the current working environment; constructing the map corresponding to the current working environment according to the motion information and the environment information collected during the wall movement; the motion information is used to represent the motion of the robot during the wall movement, and the environment information is used to represent the external environment features identified by the robot during the wall movement.

[0007] In an embodiment, determining the contour feature in the map corresponding to the current working environment comprises: fitting to generate a plurality of contour line segments based on the collision point positions and the edge point positions in the motion information; determining whether there is an error contour line segment with position information to be corrected according to the environment information and / or the preset angle range, and the included angle between each two adjacent contour line segments; and generating the map based on the correct position information and the obstacle positions in the environment information.

[0008] In an embodiment, determining the contour feature in the map corresponding to the current working environment comprises: determining whether the included angle between adjacent contour line segments is within the preset angle range; marking the included angle that is not within the preset angle range as a problem included angle, finding the wall corner position corresponding to the problem included angle in the environment information, and determining the wall corner angle corresponding to the wall corner position; and determining whether there is an error contour line segment with position information to be corrected based on the wall corner angle and the problem included angle.

[0009] In an embodiment, determining the target arch sweeping path according to the contour feature in the map corresponding to the current working environment comprises: generating a plurality of arch sweeping paths based on the contour feature in the map; each arch sweeping path comprises at least one arch sweeping route, and each arch sweeping route is composed of an arch sweeping branch or a plurality of arch sweeping branches connected end to end; and selecting the target arch sweeping path with the least total number of arch sweeping routes from all the arch sweeping paths.

[0010] In an embodiment, selecting the target arch sweeping path with the least total number of arch sweeping routes from all the arch sweeping paths comprises: determining a reference arch sweeping path with the least total number of arch sweeping routes from all the arch sweeping paths, and determining whether the number of the reference arch sweeping paths is not more than one; if not more than one, marking the reference arch sweeping path as the target arch sweeping path; and if more than one, determining at least two candidate arch sweeping paths based on a long side planning strategy; calculating the overall cleaning time length corresponding to each candidate arch sweeping path respectively, and marking the candidate arch sweeping path with the least overall cleaning time length as the target arch sweeping path.

[0011] In an embodiment, the cleaning information comprises unfinished cleaning, and the next optimal arch cleaning branch to be cleaned is determined based on the real-time position of the robot, the position information of each arch cleaning branch, and the cleaning information, comprising: based on the current orientation of the robot and the position information of each arch cleaning branch with unfinished cleaning, the cost value of moving from the real-time position to each arch cleaning branch is calculated; and the next optimal arch cleaning branch to be cleaned is determined according to the cost value.

[0012] In an embodiment, the next optimal arch cleaning branch to be cleaned is determined according to the cost value, comprising: the arch cleaning branch with the minimum cost value is marked as the first arch cleaning branch, and the robot is controlled to move towards the first arch cleaning branch; based on the latest generated map, the obstacle intrusion distance corresponding to each arch cleaning branch is calculated; it is judged whether there is a second arch cleaning branch with a cost value close to the minimum cost value and a smaller obstacle intrusion distance; if there is, the second arch cleaning branch with the smallest obstacle intrusion distance is marked as the optimal arch cleaning branch; and if there is not, the first arch cleaning branch is marked as the optimal arch cleaning branch.

[0013] In an embodiment, the cleaning information further comprises finished cleaning, and the next optimal arch cleaning branch to be cleaned is determined according to the cost value, comprising: at least one arch cleaning branch with the minimum cost value is marked as a candidate arch cleaning branch; when there are multiple candidate arch cleaning branches, the difference between the cost values of any two candidate arch cleaning branches is within a preset difference range; if there are multiple candidate arch cleaning branches, a plurality of straight-line connection paths are generated based on the real-time position of the robot and the starting points of the candidate arch cleaning branches, the number of intersection points of each straight-line connection path and the arch cleaning branches with finished cleaning is determined; the candidate arch cleaning branch corresponding to the straight-line connection path with the most intersection points is marked as the optimal arch cleaning branch; and if there is only one candidate arch cleaning branch, the candidate arch cleaning branch is marked as the optimal arch cleaning branch.

[0014] In an embodiment, the optimal connection path moving to the starting point position of the optimal arch cleaning branch is generated based on the position information of the optimal arch cleaning branch and the real-time position, comprising: based on the position information of the optimal arch cleaning branch, it is judged whether there is an outer contour wall on the straight-line connection path between the real-time position and the starting point position; if there is an outer contour wall, the starting point position and the ending point position of the optimal arch cleaning branch are exchanged, and the optimal connection path is generated based on the exchanged starting point position, the real-time position, and the position information of the obstacle; and if there is no outer contour wall, the optimal connection path is generated based on the starting point position, the real-time position, and the position information of the obstacle.

[0015] The beneficial effects of the present application compared with the prior art are:

[0016] The application can solve the problem of too long arch sweeping time and low work efficiency of the robot in the prior art due to unsuitable navigation path planning, obstacle blocking and other reasons. In the application, the robot determines a suitable target arch sweeping path based on the contour features of the environment, and determines the next optimal arch sweeping branch and the corresponding optimal connection path to be cleaned based on the real-time position, cleaning information and the position information of each arch sweeping branch after completing the cleaning work of the current branch. The application considers various factors such as the generation of the target arch sweeping path, the determination of the optimal arch sweeping branch and the generation of the optimal connection path, to minimize the time or path wasted by the robot during the execution of the arch sweeping cleaning work. The application effectively improves the work quality and work efficiency of the cleaning robot, saves the working time required by the robot in the environment, improves the utilization rate of the mobile power supply carried by the robot, makes the cleaning work of the robot in the environment standard and neat, and improves the user experience. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0018] Figure 1 The structural schematic diagram of the robot provided by an embodiment of the application;

[0019] Figure 2 The flowchart of the arch sweeping motion guiding method provided by an embodiment of the application;

[0020] Figure 3 The flowchart of the arch sweeping motion guiding method provided by an embodiment of the application;

[0021] Figure 4 The sub-flowchart of step S220 provided by an embodiment of the application;

[0022] Figure 5 The schematic diagram of the edge-following point and the collision point in the edge-following motion provided by an embodiment of the application;

[0023] Figure 6 The schematic diagram of the contour line segment fitting provided by an embodiment of the application;

[0024] Figure 7 The schematic diagram of the problem angle preliminary correction provided by an embodiment of the application;

[0025] Figure 8 The schematic diagram of the robot referring to the reference map to align the map as a whole provided by an embodiment of the application;

[0026] Figure 9 This is a schematic diagram of the original distribution of obstacles provided in an embodiment of this application;

[0027] Figure 10 This is a schematic diagram of the distribution of expansion barriers provided in an embodiment of this application;

[0028] Figure 11 A schematic diagram of a sub-process of step S230 provided in an embodiment of this application;

[0029] Figure 12 A schematic diagram of a bow sweeper path with only one bow sweeper route provided for an embodiment of this application;

[0030] Figure 13 A schematic diagram of a bow sweeper path with two bow sweeper routes provided in an embodiment of this application;

[0031] Figure 14 A schematic diagram illustrating the calculation principle of the cost value of the bow sweeper branch provided in an embodiment of this application;

[0032] Figure 15 A schematic diagram of a sub-process of step S250 provided in an embodiment of this application;

[0033] Figure 16 This is a schematic diagram illustrating the calculation principle of obstacle encroachment distance for each bow sweeper branch according to an embodiment of this application;

[0034] Figure 17 This is another sub-process diagram of step S250 provided in an embodiment of this application;

[0035] Figure 18 A schematic diagram illustrating the number of intersections between a straight connecting path and a completed sweeper branch provided in an embodiment of this application;

[0036] Figure 19 A schematic diagram of a sub-process of step S260 provided in an embodiment of this application;

[0037] Figure 20 This is a schematic diagram illustrating the straight-line connection path between the robot's real-time position and the two endpoints of the optimal bow sweeping branch, provided in an embodiment of this application.

[0038] Reference numerals: 1-Robot; 11-Environmental detection sensor; 12-Motion sensor; 13-Processor; 14-Memory; 100-Bow sweeper path; 101-Bow sweeper long side; 102-Bow sweeper short side; 103-Optimal bow sweeper path; 104-Alternative bow sweeper path; 110-Bow sweeper route; 120-Bow sweeper path; 200-Obstacle; 300-Outer contour segment. Detailed Implementation

[0039] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0040] Similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0041] The technical solution of this application will now be clearly and completely described with reference to the accompanying drawings.

[0042] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of a robot provided in one embodiment of this application. Figure 1 As shown, the robot includes at least one environmental detection sensor 11, at least one motion sensor 12, at least one processor 13, and a memory 14. Both the environmental detection sensor 11 and the motion sensor 12 are connected to the processor. The environmental detection sensor 11 is used to detect the environment in which the robot is located and generate corresponding environmental information; the motion sensor 12 is used to detect the motion of the robot during its movement and generate corresponding motion information.

[0043] Figure 1 The example uses an environmental detection sensor 11, a motion sensor 12, a processor 13, and a memory 14. The processor 13 and the memory 14 are connected, and the memory 14 stores instructions that can be executed by at least one processor 13. The instructions are executed by at least one processor 13 to cause at least one processor 13 to perform the bow sweep motion guidance method as described in the following embodiment.

[0044] Environmental sensors can be one type of sensor or a combination of multiple types. Common environmental sensors include laser sensors, vision sensors, and depth sensors. These sensors typically collect information such as the contour information, image information, and depth information within a certain range of the robot's environment, collectively referred to as environmental information. Environmental information is used to characterize the external environmental features identified by the robot during its movement.

[0045] The motion sensor can be one type of sensor or a combination of multiple types of sensors for collecting self-working data of the robot during the motion. Common motion sensors include a gyroscope, an accelerometer, an odometer, a collision sensor, an along-wall sensor, etc. The information collected by the sensors is generally rotation angle information, speed information, collision information, along-wall information, etc. of the robot during the motion, collectively referred to as motion information. The motion information is used to represent the self-motion of the robot during the along-wall motion.

[0046] In an application process, the robot carrying the environment detection sensor and the motion sensor moves in the working environment to clean the area. After the robot obtains the environment information and the motion information through the environment detection sensor and the motion sensor, a map of the environment is generated based on the environment information and the motion information, and then an arc-sweep path is generated based on the outer contour features in the map. The arc-sweep path includes at least one continuous arc-sweep line, and the arc-sweep line is composed of one or more arc-sweep branches connected end to end. When the robot starts cleaning or finishes cleaning the current arc-sweep branch, the robot determines the optimal arc-sweep branch to be cleaned next according to the position information, cleaning information, obstacle position information of each arc-sweep branch in the map or the real-time position of the robot, and determines the optimal connection path to the starting point of the optimal arc-sweep branch based on the position information of the optimal arc-sweep branch and the real-time position of the robot.

[0047] Please refer to Figure 2 , Figure 2 The flowchart of the arc-sweep motion guiding method provided by an embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, the method is applied to a robot, and the arc-sweep motion guiding method includes the following steps. Figure 2

[0048] S110: determining a target arc-sweep path according to the outer contour features in the map corresponding to the current working environment.

[0049] The outer contour refers to the outermost wall in the current working environment of the robot, and the outer contour features include the position, length, extension direction of the line segment and the included angle between adjacent line segments, etc. The target arc-sweep path refers to the optimal navigation path selected by the robot when cleaning the current working environment.

[0050] In this step, the robot determines the target arc-sweep path to be followed when performing arc-sweep cleaning work according to the outer contour features in the pre-stored map or the latest generated map during the motion of the robot, so that the efficiency of the robot cleaning work following the target arc-sweep path is the highest.

[0051] S120: determining the optimal arc-sweep branch to be cleaned next based on the real-time position of the robot, the position information and cleaning information of each arc-sweep branch.​

[0052] The target arching path includes at least one arching branch, and the robot generally moves from a starting point to an ending point of each arching branch during the arching cleaning process. The optimal arching branch refers to an arching branch selected by the robot to be most beneficial to improve work efficiency or work quality. The robot determines the optimal arching branch to be cleaned next, which is beneficial to the robot to reduce useless movement distance, or to clean the working environment more regularly and efficiently, or to avoid unnecessary movement waste of power for subsequent cleaning.

[0053] In this step, after the robot completes cleaning along the current arching branch, or when the cleaning robot just enters the current working environment to start cleaning work, the robot needs to determine the optimal cleaning path to be cleaned next based on the real-time position of the robot, the position information and cleaning information of each arching branch, so as to improve the work efficiency and work quality of the robot.

[0054] S130: Based on the position information of the optimal arching branch and the real-time position, an optimal connection path moving to the starting point position of the optimal arching branch is generated.

[0055] Each arching branch includes two end points, one of which is a starting point and the other of which is an ending point. The starting point of the optimal arching branch can be changed in real time based on the real-time movement direction of the robot, the cleaning information of each arching branch or the contour characteristics of the current working environment, or can be fixed based on a preset rule or a preset direction. The optimal connection path refers to a path that the robot prefers to follow when moving from the real-time position to the starting point position of the optimal arching branch.

[0056] In this step, the robot determines at least one connection path between the starting point position and the real-time position based on the position information of the starting point of the optimal arching branch and the real-time position of the robot, and then selects the most suitable connection path as the optimal connection path in combination with the obstacle position information in the map, the contour characteristics or other factors, so as to improve the movement efficiency of the robot moving from the current position to the starting point position of the optimal arching branch, and effectively reduce the power consumption required by the movement of the robot.

[0057] Please refer to Figure 3 , Figure 3 The flowchart of the arching movement guiding method provided by an embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, the method is applied to a robot, and the arching movement guiding method includes the following steps. Figure 3

[0058] S210: Control the robot to move a preset angle along the contour wall of the current working environment.

[0059] ​The preset angle refers to an angle covered by the robot from starting the edge-following movement (also referred to as wall-following movement) to ending the edge-following movement in the whole process of moving along the outer contour wall of the current working environment. In an embodiment, the preset angle is 360 degrees so that the robot makes a round of edge-following cleaning along the outer contour wall of the current working environment and returns to the starting point, and further generates a complete map corresponding to the current working environment according to the environment information and movement information collected in the process of the round of edge-following movement.

[0060] In other embodiments of the present application, without considering the edge-following cleaning, the robot does not need to move a round to return to the starting edge-following movement point, but only needs to move an angle less than a round to generate a complete map of the current working area in combination with the environment information and movement information collected in the process of edge-following movement.

[0061] When the robot enters the current working environment to start cleaning work, it first queries whether the corresponding map of the current working environment is stored. If yes, the outer contour wall information in the pre-stored map is obtained, and the position of the nearest outer contour wall is determined based on the real-time position of the robot; if no, the position of the nearest outer contour wall is determined by the environment detection sensor carried by the robot. Then the robot starts to move towards the nearest outer contour wall, until the collision sensor is triggered and it is determined that the robot collides with the outer contour wall. The robot records the collision point as the starting point A, drives itself to make cleaning movement along the outermost wall of the current working environment in a preset direction, and collects environment information and movement information through the edge-following sensor and the environment detection sensor in the process of edge-following movement, until the robot stops moving after returning to the starting point A.

[0062] In this step, the robot obtains the outermost edge contour information of the current working environment and the distribution information of the internal obstacles of the current working environment through edge-following movement, which is used to construct or update the map in the subsequent steps by using the SLAM method or the like.

[0063] S220: Constructing a map corresponding to the current working environment according to the movement information and environment information collected in the process of wall-following movement.

[0064] The movement information is used to represent the movement of the robot in the process of wall-following movement, and the environment information is used to represent the external environment features recognized by the robot in the process of wall-following movement. In this step, the robot obtains the feature information of each element in the map corresponding to the current working environment, such as the position and length of each section of the outer contour wall, the included angle between adjacent outer contour walls, the position and size of the obstacle, and the like, based on the movement information and environment information collected in the process of wall-following movement, and then the robot constructs the map based on the feature information of these elements to accurately plan a suitable navigation path in the subsequent steps.

[0065] Please refer toFigure 4 , Figure 4 This is a schematic diagram of a sub-process of step S220 provided in an embodiment of this application. For example... Figure 4 As shown, step S220 includes the following sub-steps S221-S223.

[0066] S221: Based on the collision point position and the edge point position in the motion information, multiple outer contour line segments are fitted and generated.

[0067] Please see Figure 5 to Figure 6 , Figure 5 A schematic diagram of edge points and collision points during edge movement provided in an embodiment of this application; Figure 6 This is a schematic diagram of the fitting of an outer contour line segment according to an embodiment of this application. Because the acquisition rates of the edge sensors and collision sensors are high, the actual distribution density of edge points and collision points should be much higher than... Figure 5 .like Figure 5 to Figure 6 As shown, Figure 5 Each dot in the map represents a collision or edge-following data point with timestamp information, showing the actual edge-following movement of the cleaning robot. To generate a corresponding map suitable for planning navigation paths, the robot uses time sequence and various timestamp information to... Figure 5 The collision points and edge points are connected to form a preliminary trajectory map.

[0068] Then, the robot uses a straight-line fitting method to fit irregularly arranged line segments, such as discontinuous or multiple bends, to obtain multiple initial outer contour line segments. For details, please refer to [example missing]. Figure 6 The diagram shows the fitting of the outer contour line segments. The straight line fitting method is based on least squares, principal component analysis, and other methods.

[0069] S222: Based on environmental information and / or a preset angle range, and the included angle between every two adjacent outer contour segments, determine whether there are any outer contour segments with positional information that need to be corrected.

[0070] Directly constructing a map for localization based on motion information along the edge can introduce errors. To improve the map's aesthetics and accuracy, the robot needs to perform angle corrections on some outer contour segments in this step, based on environmental information and / or a preset angle range.

[0071] In one embodiment, the robot determines whether the included angle between adjacent outer contour segments is within a preset angle range, marking angles outside the preset angle range as problem angles. Then, the robot searches for the corner position corresponding to the problem angle in the environmental information, or searches for the corner position corresponding to the problem corner in a reference map generated solely based on the environmental information, thereby determining the corner angle corresponding to the corner position. Finally, based on the corner angle and the problem angle, the robot determines whether there are any outer contour segments with erroneous position information requiring correction. If the corner angle differs significantly from the problem angle, then there are outer contour segments with erroneous position information requiring correction; if the corner angle is close to or even equal to the problem angle, then there are no outer contour segments with erroneous position information requiring correction.

[0072] Please see Figure 7 , Figure 7 This is a preliminary schematic diagram illustrating the correction of the included angle in an embodiment of this application. Figure 7 As shown, the robot calculates the angle between every two adjacent initial outer contour segments based on the position information of each initial outer contour segment, and determines whether the angle is within a preset angle range. The preset angle range in this embodiment is determined based on factors such as robot model, motion error, and system error. The robot performs preliminary corrections on the position information of the outer contour segments corresponding to problematic angles that are outside the preset angle range, to obtain the desired result. Figure 7 The diagram shows the preliminary correction.

[0073] Please see Figure 8 , Figure 8 This is a schematic diagram illustrating how a robot, according to an embodiment of this application, aligns itself with a reference map. For example... Figure 8 As shown, the robot counts the included angles between all adjacent outer contour segments 300. Typically, it determines whether most included angles are right angles and a small portion are not. The non-right angles are marked as problem angles. Then, the robot compares the position information of the fitted outer contour segments 300 and the problem angles with the position information of the outer contour walls and the angles of the wall corners in the reference map constructed based on environmental information after edge movement. The robot corrects the position information of the two adjacent outer contour segments 300 corresponding to wall corners with right angles but problem angles.

[0074] In step S222, the robot can also make two corrections during the execution of... Figure 7 After the corresponding correction method is applied, the corrected angle is recalculated, and the process continues with... Figure 8 The corresponding overall alignment method is used to obtain more accurate positional information of the outer contour line segments; the robot can also use only... Figure 7 or Figure 8The corresponding method, the initial outer contour line segment after fitting is corrected once, and the position information of the corrected outer contour line segment is directly obtained.

[0075] S223: generating a map based on the correct position information and the obstacle position in the environment information.

[0076] See Figure 9 to Figure 10 , Figure 9 The obstacle original distribution diagram provided by an embodiment of the present application; Figure 10 The expanded obstacle distribution diagram provided by an embodiment of the present application. As shown in Figure 9 、 Figure 10 As shown in the figure, after the robot determines the correct position information of the outer contour line segment, it generates a map based on the obstacle position in the environment information, and the specific steps are as follows.

[0077] The robot generates an along-edge map with the outer contour boundary corresponding to the current working environment based on the correct position information of the outer contour line segment 300; then fills the obstacles into the corresponding positions in the along-edge map according to the obstacle 200 position in the environment information or the obstacle position in the reference map constructed based on the environment information after the along-edge movement, and expands the coverage area of the obstacle 200 based on the body radius of the robot to match the movement limit of the robot.

[0078] In steps S210 to S220, the robot generates more accurate along-edge maps and positioning information by combining the environment information and the movement information to correct the position of the outer contour line segment. In addition, the robot also generates more beautiful and more suitable along-edge maps for planning the navigation path by means of graph closure, contour extraction algorithm and filtering out small obstacles, on the premise of retaining the contour information and obvious features of the current working environment.

[0079] S230: generating a plurality of arch scanning paths based on the outer contour features in the map, and selecting the target arch scanning path with the least total number of arch scanning routes from all the arch scanning paths.

[0080] In this step, the robot obtains the outer contour features in the map according to the existing map or the along-edge map generated based on steps S210 to S220, and considering that the position of the obstacle may change in real time, the robot generates a plurality of arch scanning paths based on the outer contour features, and each arch scanning path is used to clean all areas of the current working environment.

[0081] To improve the cleaning efficiency of the robot or the utilization rate of the mobile power supply, the robot adopts the principle of the least number of block segmentation (or the principle of the least number of arch sweeping routes) to select the target arch sweeping path with the least total number of arch sweeping routes as the target arch sweeping path. One arch sweeping path includes at least one arch sweeping route, and one arch sweeping route corresponds to one cleaning block and all arch sweeping branches in the block are continuous and uninterrupted, that is, the current working environment includes at least one cleaning block.

[0082] Please refer to Figure 11 , Figure 11 The sub-flowchart of step S230 provided by an embodiment of the present application is shown in FIG. 2B. Figure 11 As shown in FIG. 2B, step S230 includes sub-steps S231 to S234.

[0083] S231: In all arch sweeping paths, determine the reference arch sweeping path with the least total number of arch sweeping routes, and determine whether the number of reference arch sweeping paths is not more than one.

[0084] Please refer to Figure 12 , Figure 13 , Figure 12 The arch sweeping path diagram provided by an embodiment of the present application with only one arch sweeping route 110 is shown in FIG. 3A. Figure 13 The arch sweeping path diagram provided by an embodiment of the present application with two arch sweeping routes 110 is shown in FIG. 3B. Figure 12 , Figure 13 As shown in FIGS. 3A and 3B, the number of arch sweeping routes or the number of block segmentations corresponding to the arch sweeping routes is extremely important for the arch sweeping efficiency of the cleaning robot. Figure 12 In the arch sweeping path 120 in FIG. 3A, only one arch sweeping route 110 is included, that is, there is only one cleaning block in the overall region corresponding to the current working environment and the block is a connected region. The cleaning robot can sweep the entire region at one time according to the arch sweeping path 120, without switching between multiple cleaning blocks.

[0085] For the same working environment, Figure 13 The arch sweeping path 120 in FIG. 3B includes two arch sweeping routes 110, and the cleaning robot needs to jump to another cleaning block 2 after completing the cleaning of the cleaning block 1. The jumping process introduces redundant motion paths and power consumption, and the overall cleaning efficiency of the robot for the overall region of the current working environment will be greatly reduced, and more uncertain factors are introduced. Therefore, the present application preferentially selects at least one reference arch sweeping path with the least total number of arch sweeping routes in this step to further select the target arch sweeping path.

[0086] S232: If not more than one, mark the reference arch sweeping path as the target arch sweeping path.

[0087] In this step, if the number of reference arch sweeping paths selected by the robot for the current working environment is the least, and there is only one reference arch sweeping path, the robot directly marks the reference arch sweeping path as the target arch sweeping path.

[0088] S233: If there is more than one, determine at least two candidate arch sweeping paths based on the long side planning strategy.

[0089] The long side planning strategy refers to: the extension direction of the arch sweeping long side 101 in each arch sweeping route is consistent with the extension direction of the longest side of the outer contour of the cleaning block where the arch sweeping long side is located, please refer to the specific description in combination with the Figure 13 illustrated; or, the extension direction of the arch sweeping long side 101 in each arch sweeping route is consistent with the extension direction of the second longest side of the outer contour of the cleaning block where the arch sweeping long side is located, please refer to the specific description in combination with the Figure 12 illustrated; when the extension directions of the longest side and the second longest side of the outer contour of the cleaning block are the same, the robot automatically takes the direction perpendicular to the extension direction of the longest side of the outer contour as the extension direction of the second longest side.

[0090] Generally, the path planned by the robot according to the extension direction of the longer side of the block is more beautiful and scientific, and in the actual cleaning process, the robot selects the smaller block side as the basis for the direction of the arch sweeping long side 101, and the overall appearance of the generated arch sweeping path 120 is more fragmented. Therefore, the robot selects at least two candidate arch sweeping paths from the multiple reference arch sweeping paths based on the above long side planning strategy, so that the extension direction of the arch sweeping long side 101 in each arch sweeping route of the candidate arch sweeping path is consistent with the extension direction of the longest side or the second longest side of the cleaning block where the arch sweeping long side 101 is located.

[0091] S234: Calculate the overall cleaning time corresponding to each candidate arch sweeping path, and mark the candidate arch sweeping path with the least overall cleaning time as the target arch sweeping path.

[0092] In this step, the robot calculates and compares the overall cleaning time of the multiple candidate arch sweeping paths. The overall cleaning time is the cumulative sum of the cleaning time (motion time) of all arch sweeping long sides 101, the cleaning time of all arch sweeping short sides 102, and the motion time required for jumping to adjacent cleaning blocks.

[0093] For the arch sweeping path with at least one arch sweeping route 110, the calculation formula of the overall cleaning time is as follows:

[0094]

[0095] Where, T i is the cleaning time required by the robot for a certain cleaning block, with the unit of s;

[0096] The cumulative sum of the motion duration required for the robot to jump all cleaning blocks, in s; D connect The motion distance required for the robot to jump all cleaning blocks, in m; v connect The motion speed of the robot when jumping between cleaning blocks, in m / s.

[0097] Since part of the speed of the robot when jumping between cleaning blocks cannot reach the highest speed, the designer defines the jumping motion speed as v / 2 in advance, where v is the highest speed of the robot when doing stable linear motion, in m / s. In other embodiments of the present application, the jumping speed can also be defined as other speeds.

[0098] The formula for calculating the cleaning duration required for the robot for a certain cleaning block is as follows:

[0099]

[0100] Where, T i The cleaning duration required for the robot for a certain cleaning block, in s;

[0101] ∑D long The path length sum of all long sides of the arch sweep in a certain cleaning block, in m; ∑D s h ort The path length sum of all short sides of the arch sweep in a certain cleaning block, in m; v long The motion speed of the robot when cleaning the long side of the arch sweep, in m / s, generally v / 2; v is the highest speed of the robot when doing stable linear motion, in m / s. In other embodiments of the present application, the motion speeds of the robot when cleaning the long side and the short side of the arch sweep can also be defined as other values. s h ort The motion speed of the robot when cleaning the short side of the arch sweep, generally v / 4; v is the highest speed of the robot when doing stable linear motion, in m / s. In other embodiments of the present application, the motion speeds of the robot when cleaning the long side and the short side of the arch sweep can also be defined as other values.

[0102] S240: Based on the current orientation of the robot and the position information of each arch sweep branch that has not been cleaned, the cost value of moving from the real-time position to each arch sweep branch is calculated.

[0103] In this step, when the robot enters the current working environment to start cleaning, or after the robot completes the cleaning work of the current arch sweep branch, the robot calculates the cost value of moving from the real-time position to each arch sweep branch based on the real-time position, the current orientation and the position information of each arch sweep branch that has not been cleaned, so as to determine the optimal arch sweep branch to be cleaned in the subsequent step based on the cost value, the obstacle distribution position or the arch sweep branch that has been cleaned.

[0104] Please refer to Figure 14 , Figure 14This is a schematic diagram illustrating the calculation principle of the bow sweeper branch cost value provided in an embodiment of this application. (See attached diagram.) Figure 14 As shown, each bow sweep branch 100 includes a first bow sweep endpoint (Sa, coordinates (Sax, Say)), a second bow sweep endpoint (Se, coordinates (Sex, Sey)), a bow sweep midpoint (m), a vertical foot (v), and a bow sweep direction. The robot's real-time pose is (Rx, Ry, R). θ Based on the position information and real-time pose R of the bow sweeping branch, robot 1 calculates the distances to the first endpoint Ds, the second endpoint De, the midpoint Dm, and the vertical distance Dv corresponding to each bow sweeping branch 100. The calculation formulas are as follows: (3)-(6)

[0105]

[0106]

[0107]

[0108]

[0109] Among them, A, B, and C are derived from the formula of the straight line segment connecting the real-time position and the foot of the perpendicular.

[0110] Robot 1 determines the start and end points of each bow sweep path by comparing the calculated first endpoint distance Ds with the second endpoint distance De. The robot marks the endpoint corresponding to the smaller endpoint distance as the start point of its bow sweep path and the other endpoint as the end point. Additionally, since the robot has a current orientation R... θ After determining the starting point of the bow sweeping branch, the robot also needs to simultaneously calculate the corresponding rotation angle D. θ The calculation formula is as follows (7):

[0111]

[0112] Based on the real-time position and current orientation R of robot 1 θ Each bow sweep path corresponds to a minimum cost distance, also known as the cost of moving from the real-time position to each bow sweep path, denoted as D. d The formula for calculating the cost value is as follows (8):

[0113] D d = a·min(Ds,De,Dm,Dv)+b·D θ (8)

[0114] Where a and b are non-correlation coefficients, a is only related to the robot's moving speed, and b is only related to the robot's rotating speed.

[0115] S250: determining the optimal arc path to be cleaned next according to the generation value.

[0116] After the robot finishes cleaning one arc path, the robot will generally prefer the nearest arc path with the minimum generation value based on the generation value calculated in step S240. However, during the cleaning process, the robot may miss some areas, the size and location of the obstacles in the working environment may change, and other factors may also affect the selection of the next arc path by the robot based on cleaning efficiency. Therefore, the robot also needs to consider other factors in combination with the generation value to determine the optimal arc path to be cleaned next.

[0117] Please refer to Figure 15 , Figure 15 The sub-process flowchart of step S250 provided by an embodiment of the present application is shown in FIG. 6. As shown in FIG. 6, step S250 includes sub-steps S251 to S255. Figure 15

[0118] S251: mark the arc path with the minimum generation value as the first arc path, and control the robot to move towards the first arc path.

[0119] During the cleaning process, the location of the obstacles in the working environment may change, so the robot needs to detect the environmental information around the robot in real time during the cleaning process and update the edge map based on the obstacles with changed locations.

[0120] In this step, the robot first marks the arc path with the minimum generation value as the first arc path, and controls the robot to move towards the first arc path. The robot acquires the environmental information around the robot in real time during the movement, and updates the pre-stored or previously generated edge map based on the location information of the obstacles in the environment.

[0121] S252: calculate the obstacle intrusion distance corresponding to each arc path based on the latest generated map.

[0122] The obstacle intrusion distance refers to the sum of the distances between the two intersection points of the arc path and the outer contours of each obstacle when the arc path and the expanded obstacle coverage area coincide. That is, when there are multiple obstacles, the obstacle intrusion distance is the sum of the distances between the intersection points of each obstacle and the arc path on a specified arc path. If the outer contour of an obstacle is tangent to an intersection point of the arc path, the corresponding obstacle intrusion distance is 0.

[0123] Please refer to Figure 16 , Figure 16 The calculation principle diagram of the obstacle intrusion distance corresponding to each arc path provided by an embodiment of the present application is shown in FIG. 7. As shown in FIG. 7, the obstacle intrusion distance corresponding to each arc path is calculated based on the latest generated map. Figure 16 ​As shown, taking the three arch scanning branches 100 as an example, the robot calculates the total length of the overlapping line segments between the three arch scanning branches and the obstacle coverage area based on the newly generated map, i.e. Figure 16 As shown, from left to right, the three arch scanning branches 100 have similar values of the cost, and the corresponding obstacle intrusion distances are D1+D2, D3, and D4, respectively.

[0124] S253: Determine whether there is a second arch scanning branch whose cost value is close to the minimum cost value and whose obstacle intrusion distance is smaller.

[0125] When the robot cleans on a specified arch scanning branch and encounters an obstacle, the robot needs to detour along the inflated obstacle contour at the intersection of the obstacle and the specified arch scanning path until it moves to another intersection of the specified arch scanning path and the obstacle contour, and continues to clean along the specified arch scanning branch. When the robot encounters more obstacles on the arch scanning path, it will also affect the work efficiency of the robot and consume more power for detouring. Therefore, in this step, after the robot calculates the obstacle intrusion distances corresponding to each arch scanning branch 100, it needs to find and determine whether there is a second arch scanning branch whose cost value is close to the first arch scanning branch and whose obstacle intrusion distance is smaller than that of the first arch scanning branch.

[0126] In an embodiment, the difference between the cost value of the other arch scanning branch whose cost value is close to that of the first arch scanning branch and the minimum cost value should be within a preset difference range. For example, when the difference between the cost value of a certain arch scanning branch and the minimum cost value is within 15% of the minimum cost value, the cost value of the arch scanning branch is considered to be close to the minimum cost value.

[0127] S254: If there is, select the second arch scanning branch with the smallest obstacle intrusion distance as the optimal arch scanning branch.

[0128] If there is, the robot selects the second arch scanning branch whose obstacle distribution has the smallest impact on arch scanning branch cleaning as the optimal arch scanning branch to be cleaned.

[0129] S255: If there is not, mark the first arch scanning branch as the optimal arch scanning branch.

[0130] Please refer to Figure 17 , Figure 17 Another sub-process diagram of step S250 provided by an embodiment of the present application is shown. As shown in Figure 17 , step S250 includes sub-steps S256 to S259.

[0131] S256: Mark at least one arch scanning branch with the minimum cost value as a candidate arch scanning branch;

[0132] The arch scanning branch marked as the alternative arch scanning branch should have a difference value of the generation value from the minimum generation value within a preset difference value range. For example, if the difference value of the generation value of a certain arch scanning branch from the minimum generation value is within 15% of the minimum generation value, the generation value of the arch scanning branch is considered close to the minimum generation value, and the arch scanning branch is marked as the alternative arch scanning branch. In this step, the robot selects at least one alternative arch scanning branch to generate a straight-line connection path between the real-time position and each alternative arch scanning branch in the subsequent step.

[0133] S257: If there are multiple alternative arch scanning branches, multiple straight-line connection paths are generated based on the real-time position of the robot and the starting points of the alternative arch scanning branches, and the number of intersection points of each straight-line connection path and the completed cleaning arch scanning branch is determined.

[0134] Please refer to Figure 18 , Figure 18 The determination of the number of intersection points of the straight-line connection path and the completed cleaning arch scanning branch provided by an embodiment of the present application is schematically shown in the figure. Please refer to Figure 18 , the robot determines two alternative arch scanning branches 104 based on the generation value, and generates a straight-line connection path to each alternative arch scanning branch based on the starting position of the alternative arch scanning branch 104 and the real-time position of the robot, and determines the number of intersection points of the straight-line connection path and the completed cleaning arch scanning branch. Figure 18 The number of intersection points of the straight-line connection paths corresponding to the two alternative arch scanning paths from left to right in the figure and the completed cleaning arch scanning branch is 3 and 1, respectively.

[0135] S258: The alternative arch scanning branch corresponding to the straight-line connection path with the most intersection points is marked as the optimal arch scanning branch.

[0136] The robot selects the alternative arch scanning branch corresponding to the straight-line connection path with the most intersection points as the optimal arch scanning branch, so that the robot preferentially moves towards the arch scanning branch that needs to be supplemented, and avoids the distance of the connection path required by the robot to finally supplement the missed arch scanning branch becoming longer after gradually moving away from the missed arch scanning branch.

[0137] S259: If there is one alternative arch scanning branch, the alternative arch scanning branch is marked as the optimal arch scanning branch.

[0138] It should be noted that the embodiments of this application do not limit the priority level of the robot's determination of the optimal sweeping path. The robot can prioritize marking the missed sweeping path as the optimal sweeping path when the current sweeping path has not been cleaned; the robot can also prioritize marking the sweeping path with the smallest obstacle 200 encroachment distance as the optimal sweeping path; the robot can also directly determine the optimal sweeping path based on the minimum cost value, without considering the obstacle detour cost and the compensation cost of the missed sweeping path; the robot 1 can also determine multiple candidate sweeping paths with the smallest cost value based on the difference between each cost value and the minimum cost value, and on the premise of prioritizing the compensation of the missed sweeping path based on steps S256-S259, the optimal sweeping path is determined based on the obstacle encroachment distance according to steps S251-S255.

[0139] S260: Based on the location information and real-time position of the optimal bow sweeper branch, generate the optimal connection path to the starting position of the optimal bow sweeper branch.

[0140] In this step, the robot combines its real-time position, the position information of the optimal bow sweep branch, and the outer contour boundary (outer contour line segment) in the edge map to generate the optimal connection path to the starting position of the optimal bow sweep branch.

[0141] Please see Figure 19 , Figure 19 This is a schematic diagram of a sub-process of step S260 provided in an embodiment of this application. For example... Figure 19 As shown, step S260 includes sub-steps S261-S263.

[0142] S261: Based on the location information of the optimal bow sweeper branch, determine whether there is an outer contour wall on the straight connecting path between the real-time position and the starting position.

[0143] Please see Figure 20 , Figure 20 This is a schematic diagram illustrating the straight-line connection path between the robot's real-time position and the two endpoints of the optimal bow sweeper path, provided in one embodiment of this application. (See diagram below.) Figure 20 As shown, the robot generates a straight-line connecting path based on the starting position and real-time position of the optimal bow sweeping branch. Figure 20 The robot determines whether there is an outer contour wall on the straight connecting path (path 1) shown, that is, whether the straight connecting path intersects with the outer contour line segment in the map.

[0144] S262: If there is an outer contour wall, swap the starting and ending positions of the optimal bow sweeper branch, and generate the optimal connection path based on the swapped starting position, real-time position, and obstacle position information.

[0145] In one embodiment, such as Figure 20The straight connection path is shown as path 1). Figure 20 If the straight connection path (shown as path 1) intersects with the outer contour boundary (the outer contour line segment 300) of the working environment where the robot is located, the robot 1 will exchange the start position and the end position of the optimal arch sweeping branch 103, and regenerate a new straight connection path (shown as path 2) based on the exchanged start position (the original end position) and the real-time position of the robot, and mark the new straight connection path as the optimal connection path. Figure 20

[0146] In an embodiment, if there is an outer contour wall, the robot 1 can also re-determine the optimal arch sweeping branch under the condition that the cost is similar. If no other arch sweeping branch can be selected as the optimal arch sweeping branch, the robot will exchange the start position and the end position of the optimal arch sweeping branch, so that the robot moves to the end position that does not intersect with the outer contour wall first.

[0147] S263: If there is no outer contour wall, the optimal connection path is generated based on the start position, the real-time position, and the position information of the obstacle.

[0148] In an embodiment, the robot 1 also needs to determine whether there is an obstacle on the straight connection path in combination with the position information of the expanded obstacle in the newly generated map. On the premise that the straight connection paths at both ends of the optimal arch sweeping branch do not intersect with the outer contour line segment 300 (the outer contour wall), the robot can determine the optimal connection path based on the number or the length of the obstacle 200 on the straight connection path. For example, if the straight connection paths corresponding to the start position and the end position of the optimal arch sweeping branch do not intersect with the outer contour boundary of the working environment, but the length of the obstacle on the straight connection path corresponding to the start position is longer than the length of the obstacle on the straight connection path corresponding to the end position, and the difference between the distance of the start position and the distance of the end position is within a preset range, the robot should still exchange the start position and the end position of the optimal arch sweeping branch 103, so that the straight connection path corresponding to the new start position (the original end position) is used as the optimal connection path.

[0149] In this application, the robot determines a suitable target arch sweeping path based on the outer contour features of the environment, and determines the optimal arch sweeping branch and the corresponding optimal connection path to be cleaned next based on the real-time position, the cleaning information, and the position information of each arch sweeping branch after completing the cleaning work of the current branch. This application considers various factors such as the generation of the target arch sweeping path, the determination of the optimal arch sweeping branch, and the generation of the optimal connection path, to minimize the time or power wasted by the robot during the execution of the arch sweeping cleaning work.

[0150] ​The application effectively improves the working quality and efficiency of the cleaning robot, saves the working time required by the robot in the environment, improves the utilization rate of the mobile power carried by the robot, and makes the cleaning work of the robot in the environment standard and neat; in addition, the target arc-sweep path generated by the robot in real time, the cleaning situation of each arc-sweep branch and the real-time position of the robot can also be directly viewed by the user through the mobile phone APP or other UI interface, and the use experience of the user is effectively improved.

[0151] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various changes and modifications to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for guiding bow sweep motion, characterized in that, The method is applied to a robot, and the method includes: The target bow sweep path is determined based on the outer contour features in the map corresponding to the current working environment; the target bow sweep path includes at least one bow sweep branch. Based on the robot's real-time position, the position information and cleaning information of each of the bow sweeper paths, the next optimal bow sweeper path to be cleaned is determined; Based on the location information and real-time position of the optimal bow sweeper branch, an optimal connection path is generated to move to the starting position of the optimal bow sweeper branch. The step of generating an optimal connection path to the starting position of the optimal bow sweeper branch based on the location information and real-time position of the optimal bow sweeper branch includes: Based on the location information of the optimal bow sweeper branch, determine whether there is an outer contour wall on the straight connecting path between the real-time position and the starting position; If the outer contour wall exists, the starting and ending positions of the optimal bow sweeper branch are swapped, and the optimal connection path is generated based on the swapped starting position, the real-time position, and the position information of the obstacle. If the outer contour wall does not exist, the optimal connection path is generated based on the starting position, the real-time position, and the position information of the obstacle.

2. The bow sweep motion guidance method according to claim 1, characterized in that, Before determining the target bow sweep path based on the outer contour features in the map corresponding to the current working environment, the method further includes: Control the robot to move along the outer contour wall of the current working environment by a preset angle; Based on the motion information and environmental information collected during the wall-movement process, a map corresponding to the current working environment is constructed; the motion information is used to characterize the robot's own motion during the wall-movement process, and the environmental information is used to characterize the external environmental features identified by the robot during the wall-movement process.

3. The bow sweep motion guidance method according to claim 2, characterized in that, The step of constructing a map corresponding to the current working environment based on the motion information and environmental information collected during the movement along the wall includes: Based on the collision point position and the edge point position in the motion information, multiple outer contour line segments are fitted and generated. Based on the environmental information and / or the preset angle range, and the included angle between every two adjacent outer contour segments, determine whether there are any outer contour segments with positional information that need to be corrected. The map is generated based on the correct location information and the obstacle locations in the environmental information.

4. The bow sweep motion guidance method according to claim 3, characterized in that, The step of determining whether there are out-of-position error out-of-position segments that need to be corrected based on the environmental information and / or a preset angle range, and the included angle between every two adjacent out-of-position segments, includes: Determine whether the included angle between adjacent outer contour segments is within the preset angle range; Angles outside the preset angle range are marked as problem angles. The corner position corresponding to the problem angle is found in the environmental information, and the corner angle corresponding to the corner position is determined. Based on the angle between the corner and the problem, determine whether there is an error outer contour line segment in the position information that needs to be corrected.

5. The bow sweep motion guidance method according to claim 1, characterized in that, The step of determining the target bow sweep path based on the outer contour features in the map corresponding to the current working environment includes: Multiple bow sweep paths are generated based on the outer contour features in the map; each bow sweep path includes at least one bow sweep route, and each bow sweep route consists of one bow sweep branch or multiple bow sweep branches connected end to end. Among all the bow sweep paths, the target bow sweep path with the smallest total number of bow sweep routes is selected.

6. The bow sweep motion guidance method according to claim 5, characterized in that, Selecting the target bow sweep path with the minimum total number of bow sweep paths among all the bow sweep paths includes: Among all the bow sweep paths, determine the reference bow sweep path with the fewest total number of bow sweep paths, and determine whether the number of reference bow sweep paths does not exceed one. If there is no more than one, the reference bow sweep path is marked as the target bow sweep path; If there is more than one, at least two alternative bow sweep paths are determined based on the long-side planning strategy; Calculate the overall cleaning time for each of the candidate bow sweeper paths, and mark the candidate bow sweeper path with the shortest overall cleaning time as the target bow sweeper path.

7. The bow sweep motion guidance method according to claim 1, characterized in that, The cleaning information includes incomplete cleaning. The process of determining the next optimal sweeping path to be cleaned based on the robot's real-time position, the position information of each sweeping path, and the cleaning information includes: Based on the robot's current orientation and the position information of each of the uncompleted sweeping paths, the cost of moving from the real-time position to each of the sweeping paths is calculated. The optimal bow sweeper branch to be cleaned is determined based on the cost value.

8. The bow sweep motion guidance method according to claim 7, characterized in that, The step of determining the next optimal bow sweeper branch to be cleaned based on the cost value includes: The bow sweeping branch with the lowest cost is marked as the first bow sweeping branch, and the robot is controlled to move toward the first bow sweeping branch. Based on the newly generated map, calculate the obstacle encroachment distance corresponding to each of the bow sweeper branches; Determine whether there exists a second bow sweep branch whose cost value is close to the minimum cost value and whose obstacle encroachment distance is smaller; If it exists, the second bow sweep branch with the smallest obstacle encroachment distance is marked as the optimal bow sweep branch; If it does not exist, mark the first bow sweep branch as the optimal bow sweep branch.

9. The bow sweep motion guidance method according to claim 7, characterized in that, The cleaning information also includes information on completed cleaning, and the step of determining the optimal bow sweeper branch to be cleaned next based on the cost value includes: At least one of the bow sweeper branches with the lowest cost value is marked as a candidate bow sweeper branch; wherein, when there are multiple candidate bow sweeper branches, the difference in cost value between any two candidate bow sweeper branches is within a preset difference range. If there are multiple candidate bow sweeper branches, multiple straight connection paths are generated based on the robot's real-time position and the starting point of the candidate bow sweeper branches, and the number of intersections between each straight connection path and the bow sweeper branch that has been cleaned is determined. The candidate bow sweeper branch corresponding to the straight connecting path with the most intersections is marked as the optimal bow sweeper branch. If there is one candidate bow sweeper branch, mark the candidate bow sweeper branch as the optimal bow sweeper branch.

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