Navigation method considering robot deformation obstacle avoidance

Abstract

The invention provides a navigation method considering robot deformation obstacle avoidance. The navigation method is used for a single-degree-of-freedom deformation mobile robot with a known three-dimensional size relationship. Simplifying the three-dimensional environment into a two-dimensional grid map; different occupied areas of the robot in different deformation states are considered during expansion of the cost map; calculating height state information of the robot according to the special cost value of the position of the path point by adopting an improved A * algorithm to obtain a global path containing the height information of the robot; an improved DWA algorithm is adopted, robot height information of a global path is analyzed, the current motion state of the robot is judged, a speed space and a motion track space are added to a dynamic window, deformation speed sampling is set, safety sizes of the robot in different states are analyzed in obstacle cost, and the moving speed and the deformation speed of the robot are obtained. Therefore, the robot is controlled to pass through an obstacle channel with height limitation by applying a deformation function.

Description

Technical Field

[0001] The invention belongs to the technical field of robot navigation, and in particular relates to a navigation method that takes robot deformation and obstacle avoidance into consideration. Background Art

[0002] At present, deformable mobile robots are used to realize some motion functions in specific scenarios due to their good passability in complex environments. Among them, path planning is the core of mobile robot control research. The robot's navigation aims to plan a collision-free path from the starting point to the target point for the deformable mobile robot, and ensure that the robot reaches the target point safely and smoothly. In global path planning, the A* algorithm is often improved on its basis to achieve various planning purposes due to its good performance and accuracy. In local path planning, the DWA algorithm is often used to plan and control the movement of the robot due to its flexibility and real-time performance. Traditional navigation expands obstacles according to the fixed safety size of the robot before planning, and then plans the robot as a point mass. This method is not suitable for deformable mobile robots with variable sizes. Summary of the invention

[0003] In order to give full play to the advantage of the transformable robot's ability to pass through complex environments, effectively reduce the length of the planned path and control the robot to reach the target point safely and smoothly, the present invention provides a navigation method that takes robot deformation and obstacle avoidance into consideration, particularly a navigation method for a transformable wheeled mobile robot.

[0004] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a navigation method for a single-degree-of-freedom rigid plate deformable mobile robot with known three-dimensional size relationship, which takes into account the robot's deformation and obstacle avoidance, simplifies the complex three-dimensional environment into a two-dimensional grid map; considers the different footprints of the robot in different deformation states when the cost map is expanded; assigns robot height information to the global path; calculates the robot's moving speed and deformation speed, and realizes the control of the robot to apply the deformation function through an obstacle channel with height restrictions. It has the advantages of shortening the global path and smoothing the deformation change control during the robot navigation process, and has important significance and a wide range of application scenarios in the field of deformable mobile robot navigation.

[0005] The present invention discloses a navigation method that takes robot deformation into consideration for obstacle avoidance for most single-degree-of-freedom deformable mobile robots with known three-dimensional size change relationships, comprising the following steps: step S1: simplifying the three-dimensional environment according to the limit state that allows the single-degree-of-freedom deformable mobile robot to pass through, and adding multiple grayscale value information to a two-dimensional grid map according to the height restrictions of the robot in each area, thereby obtaining a two-dimensional grid map in which different gray values ​​represent different height restrictions; step S2: using multiple grayscale values ​​based on the two-dimensional grid map to assign corresponding special cost values ​​to the height restriction area, and assigning corresponding special cost values ​​to the obstacle avoidance in each area according to the corresponding circumscribed circle radius of the fuselage when the robot passes through the various height restriction areas. The expansion radius is set according to the obstacle, and a cost map layer is obtained to reflect the different height limits of the robot in each area and the safe size of each deformation state; Step S3: The A* algorithm is improved, and the robot height state information is calculated according to the special cost value of the path point, and the global path containing the robot height information is obtained; Step S4: The DWA algorithm is improved, the robot height information of the global path is analyzed, the current motion state of the robot is judged, the speed space and the motion trajectory space are added to the dynamic window, the deformation speed sampling is set, and the safe size of the robot in different states is analyzed in the obstacle cost, and the robot's moving speed and deformation speed are obtained. The present invention can control the deformable mobile machine to apply the deformation function to pass through the obstacle channel with height restrictions in a known environment. Compared with the traditional navigation method, it avoids some unnecessary detours in the navigation process, has the advantages of shortening the global path and smoothing the deformation process during the robot navigation process, and has important significance and a wide range of application scenarios in the field of deformation mobile robot navigation.

[0006] The technical solution specifically adopted by the present invention to solve the technical problem is: A navigation method for robot deformation and obstacle avoidance is proposed: for a single-degree-of-freedom deformable mobile robot with known three-dimensional size relationship; the three-dimensional environment is simplified into a two-dimensional grid map; the different footprints of the robot in different deformation states are considered when the cost map is expanded; the improved A* algorithm is used to calculate the robot height state information according to the special cost value of the path point location, and a global path containing the robot height information is obtained; the improved DWA algorithm is used to analyze the robot height information of the global path, determine the current motion state of the robot, add speed space and motion trajectory space in the dynamic window, set deformation speed sampling, and analyze the safe size of the robot in different states in the obstacle cost, and obtain the robot's moving speed and deformation speed, so as to realize the control of the robot to apply the deformation function through the obstacle channel with height restriction.

[0007] Furthermore, the simplification of the three-dimensional environment into a two-dimensional grid map is specifically as follows: the three-dimensional environment is simplified according to the limit state that allows the single-degree-of-freedom deformable mobile robot to pass, and gray value information is added to the two-dimensional grid map according to the height limit of the robot in each area, so as to obtain a two-dimensional grid map in which different gray values ​​represent different height limits: the grid is set to white, black and multiple grays: black indicates that the robot is not passable in any posture; white indicates that the robot is passable in the highest posture; different grays correspond to passable height postures.

[0008] The specific preferred setting can be: setting the grid to white, black, and gray with RGB mean values ​​from x1 to x2. Among them, white means that there are no obstacles between the current grid height from zero to the maximum height of the robot; black means that there are obstacles between the current grid height from zero to any height; gray indicates a restricted height area, which is more specifically expressed as: gray with an RGB mean value of x2 means that there are no obstacles between the current grid height from zero to the maximum critical height of the robot, and gray with an RGB mean value of x1 means that there are no obstacles between the current grid height from zero to the minimum critical height of the robot, and the height restricted area is further divided by gray with an RGB mean value between x2 and x1. Among them, x1 and x2 represent the RGB mean values ​​of the grid map that do not affect normal navigation.

[0009] Furthermore, the different footprints of the robot in different deformation states are considered when the cost map is expanded. Specifically, based on the multiple grayscale values ​​of the two-dimensional grid map, corresponding special cost values ​​are assigned to the height restricted areas, and the expansion radius is set for the obstacles in each area according to the corresponding circumscribed circle radius of the fuselage when the robot passes through various height restricted areas, so as to obtain a cost map layer that reflects the different height restrictions of the robot in each area and the safe size of each deformation state.

[0010] That is, a special expansion map layer is added to the global cost map, and a special cost value is added to the grid map obtained in step S1 for the restricted height area, and the black grid in the restricted height area is expanded. Before the deformable mobile robot enters the low restricted height area from the high or unlimited height area, it needs to lower its own height to the height limit of the next area, otherwise it cannot enter smoothly. Therefore, the cost map layer performs the following operations: First, obtain the gray information of the raster map; Then, including the white grids near the gray grid, the height restriction area is processed: determine whether there is a lower restricted height area within a certain range. If so, the current grid is assigned a special cost value according to the grayscale of the lower restricted height area; otherwise, the current grid is assigned a special cost value according to the grayscale of the current grid or no processing is required; Finally, including the black grids near the gray grids, the black grids in the height restriction area are processed: determine whether there is a lower restricted height area within a certain range. If so, the expansion radius of the black grid is calculated according to the lower height limit; otherwise, the calculation is performed according to the height limit of the current black grid area or there is no need to expand in this cost map layer. The judgment range refers to the diameter of the area occupied by the transformable robot at the lower restricted height.

[0011] Furthermore, the improved A* algorithm is used to calculate the robot's height state information according to the special cost value at the location of the path point to obtain the global path containing the robot's height information. Specifically, the A* algorithm is used to obtain the global path, and z value information is added to the global path; each path point of the global path is traversed, and the cost in the cost map layer is obtained according to the location of the path point, and the maximum pass height of the robot under the current grid cost is calculated, and the obtained height is stored in the z value of the path point.

[0012] Furthermore, the analyzing the robot height information of the global path and determining the current motion state of the robot includes performing the following operations on the obtained path points of the global path: Analyze the robot height information of the global path: locate the current global path point; if there is a path point with a z value smaller than the previous path point, it is defined as an unfolding point; if there is a path point with a z value larger than the previous path point, it is defined as a folding point; if the z values ​​of the global path points are all equal, it means that the robot does not need to deform; Determine the current motion state of the robot: calculate and obtain the current height of the robot from the robot chassis; calculate the distance s1 from the current position to the next deformation point based on the path point information corresponding to the current position and the information of the folding point and the unfolding point; then, calculate and obtain the longest deformation path length s2 of the robot based on the target height of the deformation point, the current height of the robot, the maximum driving speed of the robot and the minimum deformation speed; obtain the current folding state of the robot.

[0013] Furthermore, the method of obtaining the current folding state of the robot is specifically as follows: When the robot height is equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that it is necessary to consider whether to perform an unfolding movement to lower the height in combination with the improved dynamic window and path cost; if the path point where the robot is located is a folding point, it indicates that it is necessary to start a folding movement to reduce the footprint; when the robot height is not equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that an unfolding movement is in progress; if s1>s2 of the path point where the robot is located, it indicates that a folding movement is in progress; When the robot reaches the deployment point, if its height is not equal to the z value of the deployment point, it will stop immediately, unfold or fold on the spot, adjust its height to be equal to the z value of the deployment point, and then enter the height restriction area; When all simulated paths in the robot's dynamic window collide with obstacles, the corresponding obstacle costs are not 0, and the robot's height is not equal to the z value of the path point, it will stop immediately, expand or fold on the spot, adjust its height to be equal to the z value of its own path point, and then continue navigation movement; When the robot height is equal to the z value of the path point, the simulated paths in the robot dynamic window still collide with obstacles, and the corresponding obstacle costs are not 0, which means that an accident has occurred in the navigation. All movements should be stopped immediately and wait for manual rescue. If the robot is not in one of the above states, local planning is performed using traditional DWA.

[0014] Furthermore, the adding of the speed space and the motion trajectory space in the dynamic window is specifically as follows: For the dynamic window of the DWA algorithm during the deformation process, the velocity space and motion trajectory space are created according to the kinematic model of the deformable mobile robot. In addition to the linear velocity and angular velocity, the velocity space also adds a height change speed to define the deformation speed to control the deformation speed of the robot. The motion trajectory space is calculated by the following formula: For the dynamic window of the DWA algorithm during the deformation process, the velocity space and motion trajectory space are created according to the kinematic model of the deformable mobile robot; the motion trajectory space is calculated by the following formula: Where t represents the current time, T represents the time interval of the predicted trajectory, x, y, h r Respectively represent the x-coordinate, y-coordinate and height of the robot's position at each prediction moment, V represents the driving speed, represents the heading angle of the robot, represents the angular velocity of the robot, V h Indicates the deformation speed.

[0015] Furthermore, for the deformation speed sampling of the DWA algorithm during the deformation process, in order to ensure that the robot can deform smoothly, after generating the motion trajectory space containing x and y, the deformation height information is added to the motion trajectory space at the minimum deformation speed, and then collision detection is performed for the predicted trajectory. If all predicted trajectories are impassable, the deformation speed is increased to generate a new motion trajectory space; if all deformation speeds are impassable, it means that an accident has occurred in the navigation, and all movements are stopped immediately; For the predicted path cost of the DWA algorithm during the deformation process, when calculating the obstacle cost, the robot's size radius is determined by the h of the predicted path point.r The values ​​are obtained through three-dimensional relationship calculation of the deformable mobile robot.

[0016] Also, a single-degree-of-freedom deformable mobile robot with known three-dimensional dimensional relationship is navigated and controlled using a navigation method that takes robot deformation and obstacle avoidance into consideration as described above.

[0017] Compared with the prior art, the present invention and its preferred embodiments include at least the following outstanding features and beneficial effects: (i) The complex three-dimensional environment is simplified into a two-dimensional grid map. During the whole process, the three-dimensional size of the robot is regarded as two independent variables, height and two-dimensional size, for collision detection, which improves the search efficiency; (ii) Design a cost map layer for obstacles with height restrictions, and reasonably allocate the expansion radius of obstacles according to different height restrictions, so that the deformable mobile robot with variable sizes can still be considered as a particle for global path planning, reducing the redundant calculation of size in the global navigation process; (iii) Add the robot’s height information to the global path to more intuitively show the robot’s deformation state at different path points; (IV) Add operating logic to the DWA algorithm to cope with the deformation and change movement of the robot during navigation in different situations. Add the deformation speed and the corresponding robot height information in the velocity space and motion trajectory space of the dynamic window respectively to reasonably simulate the robot's future route and posture. In the prediction of the path obstacle cost, the robot's footprint radius under different deformation states is detected based on the robot height information in the motion trajectory space to reasonably plan the safe path of the deformable mobile robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments: Figure 1 is a navigation flow diagram of a preferred embodiment of the present invention; Figure 2 ae is a schematic diagram of converting a three-dimensional map into a two-dimensional grid map in a preferred embodiment of the present invention; Figure 3 A grid map of a preferred embodiment of the present invention; Figure 4 In the ad is the pair Figure 3 Add the cost map layer schematic diagram of the present invention; Figure 5 A schematic diagram of the relationship between the costmap layers of a preferred embodiment of the present invention; Figure 6 A global path schematic diagram of a preferred embodiment of the present invention; Figure 7Figure ag is a logic diagram of local path planning in a preferred embodiment of the present invention; Figure 8 Figures a to f are navigation simulation result diagrams of a preferred embodiment of the present invention.

[0019] In the above figure: h1-the height of the robot before entering the channel, h2-the height of the robot under the height limit; s-the diameter of the robot's footprint determined by the cost map; A-folding point; B-unfolding point; s1-the distance from the current position to the next deformation point, s2-the longest deformation path length; h-the height of the robot, z-the height of the path point.

[0020] Figure 5 Among them: a-static layer, b-obstacle layer, c-expansion layer, d-special expansion map layer, e-cost map. DETAILED DESCRIPTION

[0021] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are specifically described in detail as follows: It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0022] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0023] This embodiment provides a navigation method that takes robot deformation and obstacle avoidance into consideration, which is described based on the navigation stack of the robot operating system and specifically includes: Figure 1As shown, step S1: simplify the three-dimensional environment according to the limit state that allows the single-degree-of-freedom deformable mobile robot to pass, and add multiple gray value information to the two-dimensional grid map according to the height limit of the robot in each area, and obtain a two-dimensional grid map with different gray values ​​representing different height limits; step S2: use multiple gray values ​​based on the two-dimensional grid map to assign corresponding special cost values ​​to the height limit area, and set the expansion radius of the obstacles in each area according to the corresponding fuselage circumscribed circle radius when the robot passes through multiple height limit areas, and obtain a cost map layer to reflect the different height limits of the robot in each area and the safe size of each deformation state; step S3: improve the A* algorithm, calculate the robot height state information according to the special cost value of the path point location, and obtain the global path containing the robot height information; step S4: improve the DWA algorithm, analyze the robot height information of the global path, judge the current motion state of the robot, add the speed space and motion trajectory space in the dynamic window, set the deformation speed sampling, and analyze the safe size of the robot in different states in the obstacle cost, and obtain the robot's moving speed and deformation speed.

[0024] As a preferred solution of this embodiment, step S1 simplifies the indoor three-dimensional complex environment into a two-dimensional grid map with gray value information according to the limit state allowing the deformable mobile robot to pass, and different gray values ​​represent different obstacle height limits.

[0025] like Figure 2 The figure shows the obstacle passage with restricted passage height in this embodiment. Figure 2 a and Figure 2 c is the cross-sectional view and side view of the channel in the front direction. Its internal channel allows the robot to pass through in a certain posture, so the periphery of the obstacle is expanded into a rectangular parallelepiped, and the size is composed of the maximum length, width and height of the obstacle. The internal channel of the obstacle is shrunk into a rectangular parallelepiped channel. The size is determined by the following rules: the channel is regarded as a blank area inside the obstacle seen from the front view extending inward for a certain length, then only the width and height of the channel need to be determined; since the smaller the area occupied by the robot in the plane, the more advantages it will have in planning, and the height corresponding to the smallest two-dimensional size of the deformable mobile robot is the highest, so the height of the channel is determined from the highest height of the robot. When a certain height is selected for judgment, the maximum width expanded at this height can be obtained, such as Figure 2 As shown in the dotted box inside a, the corresponding two-dimensional dimensions of the robot at this height, length, width, and w, can be obtained. When the channel width is slightly larger than the width of the robot, it is difficult for the robot to select this path as a better direction for search in actual planning. Therefore, it is set that when the channel width satisfies When selecting the width and height to form a rectangular channel, the following is obtained after processing Figure 2b shows a simplified diagram of the obstacle. After the frontal section is processed, the following Figure 2 c is the side view of the obstacle passage. When a certain height is selected for judgment, the minimum expansion height of this passage can be obtained, such as Figure 2 As shown by the dotted line inside c, the corresponding length l and height h of the robot at this height can be obtained. r To ensure that the robot can pass through this limit state, at least in a channel with a length not less than l, the minimum height limit is set to divide the channel into segments according to a value L greater than the maximum length of the robot, and fill each segment with the minimum height of the channel, as shown below: Figure 2 Simplified diagram of the obstacle shown in d.

[0026] like Figure 2 Figure e shows the grid map of this embodiment, where the grid is set to white, black, and gray with an RGB mean value of 102 to 204. White indicates that there are no obstacles between the current grid height from zero to the maximum height of the robot; black indicates that there are obstacles between the current grid height from zero to any height; and gray indicates a restricted height area. Specifically, gray with an RGB mean value of 204 indicates that there are no obstacles between the current grid height from zero to the maximum critical height of the robot, while gray with an RGB mean value of 102 indicates that there are no obstacles between the current grid height from zero to the minimum critical height of the robot. The height restricted area is further divided by gray with an RGB mean value between 204 and 102.

[0027] Finally, the simplified obstacle height information is added to the grid map in gray to obtain the following Figure 2 e The raster map shown.

[0028] As a preferred solution of this embodiment, in step S2, based on Figure 3 The grayscale values ​​in another grid map of the present embodiment shown customize a cost map layer to reflect the footprint of the robot in different deformation states and assign special cost values ​​to reflect the height limit.

[0029] like Figure 4 As shown in a, the black grid in the restricted height area is expanded. The black grid in the restricted height area refers to the black grid connected to the gray grid in the grid map. The specific processing method is: according to the maximum passable height of the robot in the restricted height area, the length and width of the robot are obtained, and converted into the maximum circumscribed circle radius of the robot. Finally, the radius is set as the expansion radius of the obstacle, and the corresponding black grid is expanded.

[0030] In addition, before the deformable mobile robot enters a low-restricted height area from a high or unlimited height area, it needs to lower its height to within the height limit of the next area, otherwise it cannot enter smoothly. Figure 4 As shown in b, the remaining black grids nearby need to be processed: determine whether there is a lower restricted height area within a certain range. If so, calculate the expansion radius based on the lower height limit; otherwise, calculate based on the height limit of the current grid or do not need to expand in the local layer. The judgment range refers to the diameter of the area occupied by the transformable robot at the lower restricted height.

[0031] Finally, in order to enable the global path planner to recognize specific height restrictions, such as Figure 4 As shown in c, the gray grid that is not affected by the expansion is assigned a lower cost value that does not affect normal navigation according to its RGB mean value.

[0032] Similarly, before the deformable mobile robot enters the low-restricted height area from the high or unlimited height area, it needs to lower its own height to within the height limit of the next area, otherwise it cannot enter smoothly. Figure 4 As shown in d, the grids not affected by the expansion, including the nearby white grids, are further processed: determine whether there is a lower restricted height area within a certain range. If so, assign a cost value to the current grid based on the RGB mean of the lower restricted area; otherwise, calculate based on the RGB mean of the current grid or no processing is required.

[0033] like Figure 5 As shown, the cost map effect of this embodiment obtained after adding the map layer into the cost map includes a-static layer, b-obstacle layer, c-expansion layer, d-special expansion map layer, and e-cost map.

[0034] As a preferred solution of this embodiment, in step S3, a global path containing the robot height information is obtained according to the cost value of the location of the path point by improving the A* algorithm.

[0035] Use the A* algorithm to obtain the global path, traverse each path point of the global path, obtain the cost in the cost map layer obtained in step S2 according to the grid where the path point is located, calculate the maximum travel height of the robot under the current grid cost, and store the obtained height in the z value of the path point to obtain the following: Figure 6 The global path shown contains the robot's height information.

[0036] As a preferred solution of this embodiment, in step S4, the moving speed and deformation speed of the robot are calculated by using an improved DWA algorithm.

[0037] like Figure 7a to 7g are the local path planning logic diagrams of this embodiment. The current height h of the robot is calculated and obtained from the robot chassis. According to the path point information corresponding to the current position and the information of the folding point A and the unfolding point B, the distance s1 from the current position to the next deformation point is calculated. Then, according to the target height of the deformation point, the current height of the robot, the maximum driving speed of the robot and the minimum deformation speed, the longest deformation path length s2 of the robot is calculated. Combined with Figure 7 a to 7g get the current folding state of the robot: Generally, if Figure 7 As shown in Figures 7a and 7b, when the robot height h is equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that it is necessary to consider whether to perform an unfolding movement to reduce the height in combination with the improved dynamic window and path cost; if the path point where the robot is located is a folding point, it indicates that it is necessary to start a folding movement to reduce the footprint. Figure 7 As shown in Figures c and 7d, when the robot height h is not equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that the robot is in the process of unfolding movement; if s1>s2 of the path point where the robot is located, it indicates that the robot is in the process of folding movement. In special cases, such as Figure 7 As shown in Figure 5, when the robot reaches the deployment point, if the robot height h is not equal to the deployment point z value, it will stop immediately, unfold or fold in place, adjust its height to be equal to the deployment point z value, and then enter the height restriction area; in extreme cases, such as Figure 7 As shown in Figures 7f and 7g, when all simulated paths in the robot's dynamic window collide with obstacles (i.e., the obstacle costs are not 0), and the robot's height h is not equal to the path point z value, it will stop immediately, unfold or fold on the spot, adjust its own height to be equal to its own path point z value, and then continue navigation and movement; when the robot's height h is equal to the path point z value, the simulated paths in the robot's dynamic window still collide with obstacles (i.e., the obstacle costs are not 0), which means that an accident has occurred in the navigation, and all movements will be stopped immediately to wait for manual rescue. If the robot is not in any of the above states, local planning is performed using traditional DWA.

[0038] Figure 8 a to Figure 8 f is a comparison of simulation results between the traditional navigation method and the navigation method based on the Robot Operating System (ROS) navigation stack proposed by the present invention that takes robot deformation and obstacle avoidance into consideration. In the figure, the red path is the global path and the green path is the driving path. Figure 8 a and Figure 8 d is the global path planned by the traditional A* algorithm and the driving path planned by the traditional DWA algorithm in two scenarios when the robot is fully folded. Figure 8 b and Figure 8e is the global path planned by the traditional A* algorithm and the driving path planned by the traditional DWA algorithm in two scenarios when the robot is fully deployed. Figure 8 c and Figure 8 f is a deformable mobile robot. In two scenarios, the grid map and cost map provided by the present invention are used to plan a global path using the improved A* algorithm and a driving path using the improved DWA algorithm. Tables 1 and 2 show the comparison of simulation results of the traditional method and the present invention in the two scenarios. It can be found that the navigation method based on the robot operating system (ROS) navigation stack and considering robot deformation and obstacle avoidance proposed by the present invention obtains a shorter global path and takes a shorter time to reach the target point, which successfully utilizes the good passability of the single-degree-of-freedom deformable mobile robot in a complex environment.

[0039] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0040] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0041] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0042] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0043] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0044] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

[0045] The present invention is not limited to the above-mentioned optimal implementation mode. Under the inspiration of the present invention, anyone can derive other various forms of a navigation method that takes into account robot deformation and obstacle avoidance. All equal changes and modifications made within the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A navigation method for robot obstacle avoidance taking into account robot deformation, characterized in that: A single-degree-of-freedom deformable mobile robot with known three-dimensional dimensional relationship; simplifies the three-dimensional environment into a two-dimensional grid map; considers the different footprints of the robot in different deformation states when expanding the cost map; uses an improved A* algorithm to calculate the robot's height state information based on the special cost value at the location of the path point, and obtains a global path containing the robot's height information; uses an improved DWA algorithm to analyze the robot's height information of the global path, determine the robot's current motion state, add speed space and motion trajectory space to the dynamic window, set deformation speed sampling, and analyze the robot's safe size in different states in the obstacle cost to obtain the robot's moving speed and deformation speed, so as to realize the control of the robot to apply the deformation function through an obstacle channel with a height limit.

2. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 1, characterized in that: The simplification of the three-dimensional environment into a two-dimensional grid map is specifically as follows: the three-dimensional environment is simplified according to the limit state that allows the single-degree-of-freedom deformable mobile robot to pass through, and gray value information is added to the two-dimensional grid map according to the height limit of the robot in each area, so as to obtain a two-dimensional grid map in which different gray values ​​represent different height limits: the grid is set to white, black and multiple grays: black indicates that the robot is not passable in any posture; white indicates that the robot is passable in the highest posture; different grays correspond to passable height postures.

3. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 2, characterized in that: The method of considering the different footprints of the robot in different deformation states when expanding the cost map is specifically as follows: based on the multiple grayscale values ​​of the two-dimensional grid map, corresponding special cost values ​​are assigned to the height restricted areas, and the expansion radius is set for the obstacles in each area according to the corresponding circumscribed circle radius of the robot when passing through the various height restricted areas, so as to obtain a cost map layer that reflects the different height restrictions of the robot in each area and the safe size of each deformation state.

4. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 3, characterized in that: The specific operation process of cost map expansion considering different footprint sizes under different deformation states of the robot is: First, obtain the gray information of the raster map; Then, including the white grids near the gray grid, the height restriction area is processed: determine whether there is a lower restricted height area within a certain range. If so, the current grid is assigned a special cost value according to the grayscale of the lower restricted height area; otherwise, the current grid is assigned a special cost value according to the grayscale of the current grid or no processing is required; Finally, including the black grids near the gray grids, the black grids in the height restriction area are processed: determine whether there is a lower restricted height area within a certain range. If so, the expansion radius of the black grid is calculated according to the lower height limit; otherwise, it is calculated according to the height limit of the area where the current black grid is located or there is no need to expand in the current cost map layer.

5. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 4, characterized in that: The improved A* algorithm is used to calculate the robot's height state information according to the special cost value at the location of the path point to obtain the global path containing the robot's height information. Specifically, the A* algorithm is used to obtain the global path, and z value information is added to the global path; each path point of the global path is traversed, and the cost in the cost map layer is obtained according to the location of the path point, and the maximum travel height of the robot under the current grid cost is calculated, and the obtained height is stored in the z value of the path point.

6. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 5, characterized in that: The analyzing the robot height information of the global path and determining the current motion state of the robot includes performing the following operations on the obtained path points of the global path: Analyze the robot height information of the global path: locate the current global path point; if there is a path point with a z value smaller than the previous path point, it is defined as an unfolding point; if there is a path point with a z value larger than the previous path point, it is defined as a folding point; if the z values ​​of the global path points are all equal, it means that the robot does not need to deform; Determine the current motion state of the robot: calculate and obtain the current height of the robot from the robot chassis; calculate the distance s1 from the current position to the next deformation point based on the path point information corresponding to the current position and the information of the folding point and the unfolding point; then, calculate and obtain the longest deformation path length s2 of the robot based on the target height of the deformation point, the current height of the robot, the maximum driving speed of the robot and the minimum deformation speed; obtain the current folding state of the robot.

7. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 6, characterized in that: The method of obtaining the current folding state of the robot is as follows: When the robot height is equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that it is necessary to consider whether to perform an unfolding movement to lower the height in combination with the improved dynamic window and path cost; if the path point where the robot is located is a folding point, it indicates that it is necessary to start a folding movement to reduce the footprint; when the robot height is not equal to the path point z value, if s1≤s2 of the path point where the robot is located, it indicates that an unfolding movement is in progress; if s1>s2 of the path point where the robot is located, it indicates that a folding movement is in progress; When the robot reaches the deployment point, if its height is not equal to the z value of the deployment point, it will stop immediately, unfold or fold on the spot, adjust its height to be equal to the z value of the deployment point, and then enter the height restriction area; When all simulated paths in the robot's dynamic window collide with obstacles, the corresponding obstacle costs are not 0, and the robot's height is not equal to the z value of the path point, it will stop immediately, expand or fold on the spot, adjust its height to be equal to the z value of its own path point, and then continue navigation movement; When the robot height is equal to the z value of the path point, the simulated paths in the robot dynamic window still collide with obstacles, and the corresponding obstacle costs are not 0, which means that an accident has occurred in the navigation. All movements should be stopped immediately and wait for manual rescue. If the robot is not in one of the above states, DWA is used for local planning.

8. The navigation method for robot obstacle avoidance taking into account robot deformation according to claim 7, characterized in that: The specific steps of adding speed space and motion trajectory space in the dynamic window are as follows: For the dynamic window of the DWA algorithm during the deformation process, the velocity space and motion trajectory space are created according to the kinematic model of the deformable mobile robot; the motion trajectory space is calculated by the following formula: Where t represents the current time, T represents the time interval of the predicted trajectory, x, y, h r Respectively represent the x-coordinate, y-coordinate and height of the robot's position at each prediction moment, V represents the driving speed, represents the heading angle of the robot, represents the angular velocity of the robot, V h Indicates the deformation speed.

9. A navigation method for robot obstacle avoidance taking into account robot deformation according to claim 8, characterized in that: For the deformation speed sampling of the DWA algorithm during the deformation process, in order to ensure that the robot can deform smoothly, after generating the motion trajectory space containing x and y, the deformation height information is added to the motion trajectory space at the minimum deformation speed, and then collision detection is performed for the predicted trajectory. If all predicted trajectories are impassable, the deformation speed is increased to generate a new motion trajectory space; if all deformation speeds are impassable, it means that an accident has occurred in the navigation, and all movements are stopped immediately; For the predicted path cost of the DWA algorithm during the deformation process, when calculating the obstacle cost, the robot's size radius is determined by the h of the predicted path point. r The values ​​are obtained through three-dimensional relationship calculation of the deformable mobile robot.

10. A single-degree-of-freedom deformable mobile robot with known three-dimensional dimensional relationships, characterized in that: Navigation control is performed using a navigation method for robot deformation and obstacle avoidance as described in any one of claims 1 to 9.

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