A navigation method considering robot deformation obstacle avoidance

Abstract

The application provides a navigation method for a single-degree-of-freedom deformation mobile robot with known three-dimensional size relationship, which considers robot deformation obstacle avoidance; a three-dimensional environment is simplified into a two-dimensional grid map; different footprint sizes of the robot in different deformation states are considered when a cost map is inflated; an improved A* algorithm is adopted to calculate robot height state information according to special cost values of positions of path points, and a global path containing robot height information is obtained; an improved DWA algorithm is adopted to analyze robot height information of the global path, to judge a current motion state of the robot, to add speed space and motion trajectory space to a dynamic window, to set deformation speed sampling, and to analyze safe sizes of the robot in different states in obstacle cost, so that a moving speed and a deformation speed of the robot are obtained, and the robot is controlled to pass through an obstacle channel with height limitation by applying a deformation function.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of robot navigation, and particularly relates to a navigation method considering robot deformation obstacle avoidance. BACKGROUND

[0002] Currently, a deformable mobile robot is used in specific scenes to realize some motion functions due to its good passability in a complex environment, and path planning is the core of mobile robot control research. Robot navigation aims to plan a collision-free path from a starting point to a target point for the deformable mobile robot and ensure that the robot safely and smoothly reaches the target point. In global path planning, the A* algorithm is often improved on the basis thereof 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. The traditional navigation inflates obstacles according to the fixed safety size of the robot before planning, and then plans the path by regarding the robot as a mass point, which is not suitable for the deformable mobile robot with variable size. SUMMARY

[0003] In order to exert the passability advantage of the deformable robot in a complex environment, effectively reduce the length of the planned path, and control the robot to safely and smoothly reach the target point, the application provides a navigation method considering robot deformation obstacle avoidance, in particular a navigation method of a deformable wheeled mobile robot.

[0004] The application aims to overcome the shortcomings of the prior art, provide a navigation method considering robot deformation obstacle avoidance for a single-degree-of-freedom hard plate deformable mobile robot with known three-dimensional size relationship, simplify the complex three-dimensional environment into a two-dimensional grid map, consider different footprint sizes of the robot in different deformation states when inflating the cost map, assign the robot height information to the global path, calculate the movement speed and deformation speed of the robot, and realize control of the robot to pass through the obstacle channel with height limitation by applying the deformation function. The application has the advantages of shortening the global path, smoothing the deformation change control in the robot navigation process, and the like, and has important significance and a wide application scene in the field of deformable mobile robot navigation.

[0005] The application discloses a navigation method for a single-degree-of-freedom deformation mobile robot with a known three-dimensional size change relationship, and considers robot deformation obstacle avoidance, and comprises the following steps: step S1: a three-dimensional environment is simplified according to a limit state allowing a single-degree-of-freedom deformable mobile robot to pass, and a plurality of gray value information is added to a two-dimensional grid map according to the height limit of the robot in each region, so that a two-dimensional grid map with different gray values representing different height limits is obtained; step S2: based on the plurality of gray values of the two-dimensional grid map, a corresponding special cost value is given to the height limit region, and an inflation radius of an obstacle is set according to the corresponding body circumscribed circle radius of the robot passing through a plurality of height limit regions, so that a cost map layer is obtained to reflect the different height limits of the robot in each region and the safe size under each deformation state; step S3: the A* algorithm is improved, the robot height state information is calculated according to the special cost value of the position of the path point, and a global path containing 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 under different states is analyzed in the obstacle cost, so that the moving speed and the deformation speed of the robot are obtained. The application can control the deformable mobile robot to pass through an obstacle channel with a height limit by using the deformation function in a known environment, compared with a traditional navigation method, some redundant detours in the navigation process are avoided, the global path is shortened, the deformation process in the robot navigation process is smooth, and the application has important significance and a wide application scene in the field of deformation mobile robot navigation.

[0006] The technical scheme specifically adopted by the application to solve the technical problems is:

[0007] A navigation method considering robot deformation obstacle avoidance: for a single-degree-of-freedom deformation mobile robot with a known three-dimensional size relationship; a three-dimensional environment is simplified into a two-dimensional grid map; different footprint sizes under different deformation states of the robot are considered when the cost map is inflated; an improved A* algorithm is used to calculate the robot height state information according to the special cost value of the position of the path point, and a global path containing robot height information is obtained; an improved DWA algorithm is used to analyze the robot height information of the global path, judge the current motion state of the robot, add speed space and motion trajectory space to the dynamic window, set deformation speed sampling, and analyze the safe size of the robot under different states in the obstacle cost, so as to obtain the moving speed and deformation speed of the robot, so as to control the robot to pass through an obstacle channel with a height limit by using the deformation function.

[0008] Further, the simplifying the three-dimensional environment into a two-dimensional grid map specifically comprises: simplifying the three-dimensional environment according to a limit state allowing single-degree-of-freedom deformable mobile robot to pass, and adding gray value information to the two-dimensional grid map according to the height limit of each region on the robot, to obtain a two-dimensional grid map with different gray values representing different height limits; the grid is set to white, black and multiple grays; black represents that the robot cannot pass in any attitude; white represents that the robot can pass in the highest attitude; different grays correspond to height attitudes that can pass.

[0009] Specifically, the preferred setting can be that the grid is set to white, black and gray with RGB average value x1 to x2. Among them, white represents that there is no obstacle between the current grid height from zero to the maximum height of the robot; black represents that there is an obstacle from zero to any height; gray represents a height limit area, more specifically, gray with RGB average value x2 represents that there is no obstacle between the current grid height from zero to the maximum critical height of the robot, and gray with RGB average value x1 represents that there is no obstacle between the current grid height from zero to the minimum critical height of the robot, and the gray with RGB average value between x2 and x1 further divides the height limit area. Among them, x1 and x2 represent the RGB average value of the grid map that does not affect normal navigation.

[0010] Further, the consideration of different footprint sizes of the robot in different deformation states during inflation of the cost map specifically comprises: based on the multiple gray values of the two-dimensional grid map, special cost values are given to the height limit area, and the inflation radius of the obstacle is set according to the corresponding body circumscribed circle radius of the robot passing through multiple height limit areas, to obtain a cost map layer reflecting the different height limits of the robot in each region and the safe size of each deformation state.

[0011] That is, a special inflation map layer is added to the global cost map, which is specially added to the height limit area in the grid map obtained in step S1, and the black grid in the height limit area is processed. Because before the deformable mobile robot enters a low height limit area from a high or no height limit area, the height of the robot needs to be reduced to within the height limit of the next area, otherwise it cannot enter smoothly, so the cost map layer performs the following operations:

[0012] Firstly, the gray information of the grid map is obtained;

[0013] Then, the white grid containing the gray grid near the white grid is processed: it is judged whether there is a lower limit height area within a certain range, if there is, the current grid is given a special cost value according to the gray degree of the lower limit height area; otherwise, the special cost value is given according to the gray degree of the current grid or no processing is needed;

[0014] Finally, the black grid in the height limit area, including the black grid near the gray grid, is processed: it is judged whether there is a lower limit height area in a certain range, if there is, the black grid calculates the inflation radius according to the lower height limit; otherwise, the calculation is performed according to the height limit of the area where the current black grid is located or no inflation is needed in the current cost map layer. The judgment range refers to the footprint diameter of the morphing robot under the lower limit height.

[0015] Further, the improved A* algorithm is used to calculate the robot height state information according to the special generation value of the position of the path point, and the global path containing the robot height information is obtained, which specifically comprises: obtaining the global path by using the A* algorithm, and adding z value information to the global path; traversing each path point of the global path, obtaining the cost in the cost map layer according to the position of the path point, and calculating the maximum passing height of the robot under the current grid cost, and storing the obtained height into the z value of the path point.

[0016] Further, the robot height information of the global path is analyzed, and the current motion state of the robot is judged, which comprises the following operations on the path points of the obtained global path:

[0017] Analyzing the robot height information of the global path: locating the current global path point; if the z value of the path point is less than that of the previous path point, it is defined as an unfolding point; if the z value of the path point is greater than that of the previous path point, it is defined as a folding point; if the z values of the global path points are all equal, it is indicated that the robot does not need to be deformed;

[0018] Judging the current motion state of the robot: calculating and obtaining the current height of the robot from the robot chassis; calculating the distance s1 from the current position to the next deformation point according to the path point information corresponding to the current position and the information of the folding point and the unfolding point; then, calculating and obtaining the longest deformation path length s2 of the robot 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; obtaining the current folding state of the robot.

[0019] Further, the current folding state of the robot is obtained, which specifically comprises:

[0020] When the robot height is equal to the z value of the path point, if the s1 of the path point where the robot is located is less than or equal to s2, it is indicated that whether to perform unfolding motion to reduce the height needs to be considered in combination with the improved dynamic window and path cost; if the path point where the robot is located is a folding point, it is indicated that the folding motion needs to be started to reduce the footprint size; when the robot height is not equal to the z value of the path point, if the s1 of the path point where the robot is located is less than or equal to s2, it is indicated that the unfolding motion is being performed; if the s1 of the path point where the robot is located is greater than s2, it is indicated that the folding motion is being performed.

[0021] When the robot reaches the deployment point, if the robot height is not equal to the deployment point z value, stop immediately, deploy or fold in place, adjust the height to be equal to the deployment point z value, and then enter the height limit area;

[0022] When the simulated paths in the robot's dynamic window all collide with obstacles, the corresponding obstacle costs are all not 0, and the robot height is not equal to the path point z value, stop immediately, deploy or fold in place, adjust the height to be equal to the path point z value, and then continue to navigate;

[0023] When the robot height is equal to the path point z value, and the simulated paths in the robot's dynamic window still all collide with obstacles, the corresponding obstacle costs are all not 0, it means that the navigation has an accident, stop all movements immediately and wait for manual rescue;

[0024] If the robot is not in one of the above states, the traditional DWA is used for local planning.

[0025] Further, the adding of velocity space and motion trajectory space in the dynamic window is specifically:

[0026] For the dynamic window of the DWA algorithm in the deformation process, a velocity space and a motion trajectory space are created according to the kinematic model of the deformation mobile robot. The velocity space increases a height change velocity in addition to the linear velocity and angular velocity to define the deformation velocity, so as to control the deformation velocity of the robot. The motion trajectory space is calculated by the following formula:

[0027] For the dynamic window of the DWA algorithm in the deformation process, a velocity space and a motion trajectory space are created according to the kinematic model of the deformation mobile robot. The motion trajectory space is calculated by the following formula:

[0028]

[0029] Where t represents the current time, T represents the time interval of the predicted trajectory, x, y, h r represent the x coordinate, y coordinate and height of the pose of the robot at each predicted time respectively, V represents the driving speed, represents the heading angle of the robot, represents the angular velocity of the robot, V h represents the deformation velocity.

[0030] Further, in order to ensure that the robot can deform smoothly, the minimum deformation speed is added to the motion trajectory space to add the deformation height information to the motion trajectory space, and then the collision detection is performed on the predicted trajectory, if all the predicted trajectories cannot pass, the deformation speed is increased to generate a new motion trajectory space, if all the deformation speeds cannot pass, it means that the navigation is abnormal, and all the motions are stopped immediately.

[0031] For the predicted path cost of the DWA algorithm in the deformation process, when calculating the obstacle cost, the size radius of the robot is obtained by the three-dimensional relationship calculation of the h r of the predicted path point.

[0032] In addition, a single-degree-of-freedom deformable mobile robot with a known three-dimensional size relationship adopts the navigation method for considering robot deformation obstacle avoidance as described above to perform navigation control.

[0033] Compared with the prior art, the present application and the preferred schemes thereof at least include the following outstanding features and beneficial effects:

[0034] (1) The complex three-dimensional environment is simplified into a two-dimensional grid map, and the three-dimensional size of the robot is regarded as two independent variables of height and two-dimensional size for collision detection in the whole process, thereby improving the search efficiency;

[0035] (2) A cost map layer is designed for the height-limited obstacle, and the obstacle inflation radius is reasonably allocated according to different height limitations, so that the deformable mobile robot with variable size can still be regarded as a particle for planning in the global path planning, thereby reducing the redundant calculation about the size in the global navigation process;

[0036] (3) The height information of the robot is added to the global path, and the deformation state of the robot at different path points is more intuitively represented;

[0037] (4) The running logic is added to the DWA algorithm to deal with the deformation change motion in the robot navigation process in different occasions, the deformation speed and the corresponding robot height information are added to the speed space and the motion trajectory space of the dynamic window to reasonably simulate the future route and posture of the robot, and the footprint radius of the robot in different deformation states is detected according to the robot height information of the motion trajectory space in the predicted path obstacle cost to reasonably plan the safe path of the deformable mobile robot. BRIEF DESCRIPTION OF DRAWINGS

[0038] The present application will be further described in detail below in combination with the drawings and specific embodiments:

[0039] Figure 1Navigation flow diagram of preferred embodiment of the present application;

[0040] Figure 2 Fig. 2 is a diagram showing the conversion of a three-dimensional map into a two-dimensional grid map according to a preferred embodiment of the present application;

[0041] Figure 3 Fig. 3 is a grid map according to a preferred embodiment of the present application;

[0042] Figure 4 Fig. 4 is a diagram showing the relationship between the layers of the cost map according to a preferred embodiment of the present application; Figure 3 Fig. 5 is a diagram showing the addition of a cost map layer according to a preferred embodiment of the present application;

[0043] Figure 5 Fig. 6 is a diagram showing the relationship between the layers of the cost map according to a preferred embodiment of the present application;

[0044] Figure 6 Fig. 7 is a diagram showing a global path according to a preferred embodiment of the present application;

[0045] Figure 7 Fig. 8 is a diagram showing the local path planning logic according to a preferred embodiment of the present application;

[0046] Figure 8 Fig. 9 is a diagram showing the navigation simulation results according to a preferred embodiment of the present application.

[0047] In the above figures:

[0048] h1 - height of robot before entering the passage, h2 - height of robot under height restriction; s - footprint diameter of robot determined by cost map;

[0049] A - folding point; B - unfolding point; s1 - distance from current position to next deformation point, s2 - length of longest deformation path; h - height of robot, z - height of path point.

[0050] Figure 5 In the above figures: a - static layer, b - obstacle layer, c - inflation layer, d - special inflation map layer, e - cost map. DETAILED DESCRIPTION

[0051] In order to make the features and advantages of the present application more apparent, the following embodiments are described in detail as follows:

[0052] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0053] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, components, and / or groups thereof, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0054] The embodiment provides a navigation method considering robot deformation obstacle avoidance, which is based on a robot operating system navigation stack and specifically comprises: Figure 1 As shown in the figure, step S1: a three-dimensional environment is simplified according to a limit state allowing a single-degree-of-freedom deformable mobile robot to pass, and a two-dimensional grid map is added with multiple gray value information according to the height limit of the robot in each area, so that a two-dimensional grid map with different gray values representing different height limits is obtained; step S2: based on the multiple gray values of the two-dimensional grid map, a corresponding special cost value is given to the height limit area, and the inflation radius of the obstacle in each area is set according to the corresponding body circumscribed circle radius of the robot passing through multiple height limit areas, so that a cost map layer is obtained to reflect the different height limits of the robot in each area and the safety size under 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 position of the path point, so that a global path containing 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 velocity space and motion trajectory space are added in the dynamic window, the deformation velocity sampling is set, and the safety size of the robot under different states is analyzed in the obstacle cost, so that the moving speed and deformation speed of the robot are obtained.

[0055] As a preferred scheme of the embodiment, step S1 simplifies the indoor three-dimensional complex environment to 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.

[0056] As shown in the figure, step S1: a three-dimensional environment is simplified according to a limit state allowing a single-degree-of-freedom deformable mobile robot to pass, and a two-dimensional grid map is added with multiple gray value information according to the height limit of the robot in each area, so that a two-dimensional grid map with different gray values representing different height limits is obtained; step S2: based on the multiple gray values of the two-dimensional grid map, a corresponding special cost value is given to the height limit area, and the inflation radius of the obstacle in each area is set according to the corresponding body circumscribed circle radius of the robot passing through multiple height limit areas, so that a cost map layer is obtained to reflect the different height limits of the robot in each area and the safety size under 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 position of the path point, so that a global path containing 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 velocity space and motion trajectory space are added in the dynamic window, the deformation velocity sampling is set, and the safety size of the robot under different states is analyzed in the obstacle cost, so that the moving speed and deformation speed of the robot are obtained. Figure 2 Figure 2 a and Figure 2 ​c is the cross section and side view of the front direction of the channel, the internal channel allows the robot to pass in a certain posture, so the periphery of the obstacle is inflated into a cuboid, the size is composed of the maximum length, width and height of the obstacle, the internal channel of the obstacle is shrunk into a cuboid channel, and the size is determined by the following rules: the channel is regarded as the internal blank area of the obstacle seen from the front view extending inward for a 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 advantageous it is in planning, and the two-dimensional size of the deformable mobile robot is the smallest, the corresponding height 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 the dashed box in the inside of a, and the corresponding two-dimensional size length l and width w of the robot at this height can also be obtained, when the channel width is slightly larger than the width of the robot, it is difficult for the robot to choose this path as the optimal direction for search in actual planning, so when the channel width satisfies , the width and height are selected to form a cuboid channel, and after processing, the obstacle simplified diagram as shown in Figure 2 b is obtained. After processing the cross section of the front direction, the obstacle channel side view as shown in Figure 2 c is obtained. When a certain height is selected for judgment, the minimum expanded height of the channel can be obtained, such as Figure 2 the dashed line in the inside of c, and the corresponding size length l and height h of the robot at this height r , in order to ensure that the robot can pass through in this limit state, at least the minimum height limit in the channel with a length not less than l is ensured, so the channel is segmented according to a value L greater than the maximum length of the robot, and the lowest height in each segment is filled to obtain the obstacle simplified diagram as shown in Figure 2 d.

[0057] As shown in Figure 2 e, the grid map of the embodiment is set to white, black and gray with RGB average value of 102 to 204. Among them, white represents that there is no obstacle from zero to the maximum height of the robot in the current grid height; black represents that there is an obstacle from zero to any height in the current grid height; gray represents the height limit area, more specifically: gray with RGB average value of 204 represents that there is no obstacle from zero to the maximum critical height of the robot in the current grid height, and gray with RGB average value of 102 represents that there is no obstacle from zero to the minimum critical height of the robot in the current grid height, and the height limit area is further divided by gray with RGB average value between 204 and 102.

[0058] Finally, the height information of the simplified obstacle is added to the grid map in gray to obtain Figure 3e shows the grid map.

[0059] As a preferred scheme of the embodiment, in step S2, based on Figure 4 The gray value in another grid map of the embodiment shown in the figure defines a cost map layer to reflect the footprint size of the robot in different deformation states and give special cost values to reflect height restrictions.

[0060] As shown in Figure 4 a, the black grid in the height-restricted area is dilated, and the black grid in the height-restricted area refers to the black grid connected with the gray grid in the grid map. The specific processing method is: according to the maximum passable height of the robot in the height-restricted area, the corresponding length and width size of the robot is obtained, and the maximum circumscribed circle radius of the robot is converted, and finally the radius is set as the inflation radius of the obstacle, and the corresponding black grid is dilated.

[0061] In addition, before the deformable mobile robot enters a low-height-restricted area from a high or no-height-restricted area, the height of the robot needs to be reduced to within the height limit of the next area, otherwise it cannot enter smoothly. Therefore, as shown in Figure 4 b, the remaining black grids in the vicinity need to be processed: it is judged whether there is a lower height-restricted area within a certain range. If there is, the inflation radius is calculated according to the lower height restriction; otherwise, the inflation is not needed in the local layer or the calculation is performed according to the height restriction of the current grid. The judgment range refers to the footprint diameter of the deformable robot under the lower height restriction.

[0062] Finally, in order to enable the global path planner to identify the specific height restriction, as shown in Figure 4 c, the gray grid not affected by the inflation is given a lower cost value that does not affect normal navigation according to its RGB average value.

[0063] Similarly, since before the deformable mobile robot enters a low-height-restricted area from a high or no-height-restricted area, the height of the robot needs to be reduced to within the height limit of the next area, otherwise it cannot enter smoothly, therefore, as shown in Figure 5 d, the grid not affected by the inflation, including the nearby white grid, is further processed: it is judged whether there is a lower height-restricted area within a certain range. If there is, the cost value is given to the current grid according to the RGB average value of the lower height-restricted area; otherwise, the processing is not needed or the calculation is performed according to the RGB average value of the current grid.

[0064] As shown in Figure 6 the effect of the cost map of the embodiment obtained after adding the map layer into the cost map, including a-static layer, b-obstacle layer, c-inflation layer, d-special inflation map layer, and e-cost map.

[0065] As a preferred scheme of the embodiment, in step S3, the global path containing the robot height information is obtained according to the cost value of the position of the path point by improving the A* algorithm.

[0066] The global path is obtained by using the A* algorithm, each path point of the global path is traversed, the cost in the cost map layer obtained in step S2 is obtained according to the grid where the path point is located, the maximum passing height of the robot under the current grid cost is calculated, the obtained height is stored in the z value of the path point, and the global path containing the robot height information as shown in Figure 7 is obtained.

[0067] As a preferred scheme of the embodiment, in step S4, the moving speed and the deformation speed of the robot are calculated by the improved DWA algorithm.

[0068] As shown in Figure 7 a to 7g are schematic diagrams of the local path planning logic of the 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, the maximum deformation path length s2 of the robot is calculated and obtained 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. In combination with Figure 7 a to 7g, the current folding state of the robot is obtained: generally, as shown in Figure 7 a and 7b, when the robot height h is equal to the z value of the path point, if s1≤s2 of the path point where the robot is located, it is indicated that whether to perform the unfolding motion to reduce the height needs to be considered in combination with the improved dynamic window and the path cost; if the path point where the robot is located is the folding point, it is indicated that the folding motion needs to be started to reduce the footprint size. As shown in Figure 7 c and 7d, when the robot height h is not equal to the z value of the path point, if s1≤s2 of the path point where the robot is located, it is indicated that the unfolding motion is being performed; if s1>s2 of the path point where the robot is located, it is indicated that the folding motion is being performed. In a special case, as shown in Figure 7 e, when the robot reaches the unfolding point, the robot height h is not equal to the z value of the unfolding point, then it is immediately stopped, unfolded or folded in place, the height of the robot is adjusted to be equal to the z value of the unfolding point, and then the robot enters the height limited area; in an extreme case, as shown in Figure 8As shown in FIGS. 7f and 7g, when the simulation paths in the robot dynamic window all collide with obstacles (i.e., the obstacle costs are all not 0) and the robot height h is not equal to the path point z value, stop immediately, deploy or fold in place, adjust the height to be equal to the path point z value, and then continue to move; when the robot height h is equal to the path point z value, the simulation paths in the robot dynamic window still all collide with obstacles (i.e., the obstacle costs are all not 0), which indicates that the navigation has an accident, stop all movements immediately, and wait for manual rescue. If the robot is not in any of the above states, the traditional DWA is used for local planning.

[0069] Figure 8 a to Figure 8 f is a simulation result comparison between the traditional navigation method and the navigation method provided by the application based on the robot operating system (ROS) navigation stack considering robot deformation obstacle avoidance. The red path in the figure is the global path, and the green path is the driving path. Among them 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 with the robot fully folded, Figure 8 b and Figure 8 e is the global path planned by the traditional A* algorithm and the driving path planned by the traditional DWA algorithm in two scenarios with the robot fully unfolded, Figure 8 c and Figure 1 f is a deformable mobile robot, which is equipped with a grid map and a cost map provided by the application in two scenarios, and the global path is planned by the improved A* algorithm and the driving path is planned by the improved DWA algorithm. Table 1 and Table 2 show the simulation result comparison between the traditional method and the application in two scenarios. It can be found that the global path obtained by the navigation method provided by the application based on the robot operating system (ROS) navigation stack considering robot deformation obstacle avoidance is shorter, and the time to reach the target point is also shorter, which successfully utilizes the good passability of the single-degree-of-freedom deformable mobile robot in complex environments.

[0070]

[0071] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take 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 code.

[0072] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0073] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0074] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. ​ The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0075] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the present application shall have the common meaning understood by one of ordinary skill in the art to which the present application pertains. The terms "first", "second", and similar terms are used herein to distinguish one element from another, but do not necessarily have an ordinal or chronological significance. The terms "comprise", "comprising", "include", "including" and the like are used herein to indicate the presence of the stated element or elements but do not preclude the presence of one or more other elements. The terms "connected", "coupled", and the like are used herein to indicate either a direct connection, an indirect connection or an electrical connection between elements, and can include the presence of wired or wireless connection between the elements. The terms "upper", "lower", "left", "right", and the like are used herein only to represent relative positions, and can change accordingly when the absolute positions of the described objects are changed.

[0076] The above merely describes preferred embodiments of the present application, and is not intended to limit the present application in other forms. Any person skilled in the art can make changes or modifications to the above disclosed technical contents to obtain equivalent embodiments. However, any simple modification, equivalent change and modification made to the above embodiments without departing from the technical solution of the present application and according to the technical essence of the present application shall still fall within the protection scope of the present application.

[0077] The present application is not limited to the above preferred embodiments, and any person can derive other various forms of a navigation method considering robot deformation obstacle avoidance under the inspiration of the present application. Any equivalent change and modification made within the scope of the present application shall fall within the scope of the present application.

Claims

1. A navigation method considering robot deformation and obstacle avoidance, characterized in that: This method is used for single-DOF deformable mobile robots with known 3D dimensional relationships. The 3D environment is simplified to a 2D grid map. Different footprint sizes are considered during cost map inflation for different robot deformation states. An improved A* algorithm is used to calculate robot height state information based on the specific cost of pathpoint locations, resulting in a global path containing robot height information. An improved DWA algorithm is employed to analyze the robot height information of the global path, determine the robot's current motion state, add velocity and trajectory spaces to the dynamic window, set deformation velocity sampling, and analyze the safe dimensions of the robot under different states within the obstacle cost to obtain the robot's movement and deformation speeds. This enables the robot to use deformation functions to pass through obstacle channels with height restrictions. The process of simplifying the three-dimensional environment into a two-dimensional grid map involves: simplifying the three-dimensional environment according to the limit states that allow a single-degree-of-freedom deformable mobile robot to pass through, and adding grayscale information to the two-dimensional grid map based on the height restrictions of each area on the robot, so as to obtain a two-dimensional grid map where different grayscale values ​​represent different height restrictions: the grid is set to white, black, and multiple grayscale values: black indicates that the robot cannot pass through in any posture; white indicates that the robot can pass through in the highest posture; different grayscale values ​​correspond to the height postures that can be passed through. The specific steps of considering different footprints of the robot under different deformation states when inflating the cost map are as follows: based on multiple gray values ​​of the two-dimensional grid map, a corresponding special cost value is assigned to the height restriction area, and the expansion radius of the obstacles in each area is set according to the radius of the outer circle of the robot body when the robot passes through multiple height restriction areas, so as to obtain a cost map layer that reflects the different height restrictions and safety dimensions of the robot under different deformation states in each area. The specific process of map inflation, considering the cost of different footprint sizes under different robot deformation states, is as follows: First, obtain the grayscale information of the raster map; Then, the height restriction area, including the white grid near the gray grid, is processed: it is determined whether there is a lower height restriction area within a certain range. If there is, the current grid is assigned a special value based on the gray level of the lower height restriction area; otherwise, the current grid is assigned a special value based on the gray level of the current grid or no processing is required. Finally, including the black graticles near the gray graticles, the black graticles within the height restriction area are processed: it is determined whether there is a lower height restriction area within a certain range. If there is, the expansion radius of the black graticle is calculated based on the lower height restriction; otherwise, it is calculated based on the height restriction of the area where the current black graticle is located, or expansion is not required in this cost map layer. The improved A* algorithm is used to calculate the robot's height state information based on the specific cost of the path point's location, and obtain a global path containing the robot's height information. Specifically, the global path is obtained by using the A* algorithm and adding z-value information to the global path; each path point of the global path is traversed, and the cost in the cost map layer is obtained based on the path point's location. The maximum passage 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.

2. The navigation method considering robot deformation and obstacle avoidance according to claim 1, characterized in that: The process of analyzing the robot's height information in the global path and determining the robot's current motion state includes performing the following operations on the path points of the obtained global path: Analyze the robot's height information on the global path: locate the current global path point; if a path point has a z-value less than its previous path point, it is defined as an unfold point; if a path point has a z-value greater than its previous path point, it is defined as a fold point. If the z-values ​​of all global path points are equal, it means that the robot does not need to deform. Determine the robot's current motion state: Calculate and obtain the robot's current height 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 and unfolding points; then, calculate and obtain the robot's longest deformation path length s2 based on the target height of the deformation point, the robot's current height, the robot's maximum travel speed, and the minimum deformation speed; obtain the robot's current folding state.

3. The navigation method considering robot deformation and obstacle avoidance according to claim 2, characterized in that: The specific steps for obtaining the robot's current folding state are as follows: When the robot height is equal to the z-value of the path point, if s1≤s2 of the path point, it indicates that an unfolding motion to reduce the height should be considered in conjunction with the improved dynamic window and path cost; if the path point is a folding point, it indicates that a folding motion should be started to reduce the footprint. When the robot height is not equal to the z-value of the path point, if s1≤s2 of the path point, it indicates that an unfolding motion is in progress; if s1>s2 of the path point, it indicates that a folding motion is in progress. When the robot arrives at the deployment point, if the robot's height is not equal to the deployment point's z-value, it will stop immediately, deploy or fold in place, adjust its height to be equal to the deployment point's z-value, and then enter the height-restricted area. When all simulated paths in the robot's dynamic window collide with obstacles, the corresponding obstacle costs are not zero, and the robot's height is not equal to the z-value of the path point, the robot should stop immediately, unfold or fold in place, adjust its height to be equal to its own path point z-value, and then continue navigation and movement. When the robot's height equals the z-value of the path point, the simulated path in the robot's dynamic window still collides with obstacles, and the corresponding obstacle costs are not 0. This indicates that the navigation has failed, and all movement should be stopped immediately, awaiting manual rescue. If the robot is not in any of the above states, then local planning is performed using DWA.

4. The navigation method considering robot deformation and obstacle avoidance according to claim 3, characterized in that: The specific steps for adding velocity space and motion trajectory space to the dynamic window are as follows: For the dynamic window of the DWA algorithm during deformation, a velocity space and a trajectory space are created based on the kinematic model of the deformable mobile robot; the trajectory space is calculated by the following formula: Where t represents the current time, T represents the time interval for predicting the trajectory, and x, y, h r Let x, y, and height represent the robot's pose at each predicted time point, respectively, and V represent the travel speed. V represents the robot's heading angle, ω represents the robot's angular velocity, and V represents the robot's angular velocity. h Indicates the deformation rate.

5. A navigation method considering robot deformation and obstacle avoidance according to claim 4, characterized in that: To ensure the robot can deform smoothly, the deformation speed of the DWA algorithm is sampled during the deformation process. After generating the motion trajectory space containing x and y, deformation height information is added to the motion trajectory space at the minimum deformation speed. Then, collision detection is performed on the predicted trajectory. If all predicted trajectories are impassable, the deformation speed is increased and a new motion trajectory space is generated. If all deformation speeds are impassable, it indicates that the navigation has failed and all movements are stopped immediately. Regarding the predicted path cost of the DWA algorithm during deformation, when calculating the obstacle cost, the robot's radius is determined by the h value of the predicted path point. r The values ​​are obtained through three-dimensional relationship calculations of the deformable mobile robot.

6. 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 that considers robot deformation and obstacle avoidance as described in any one of claims 1-5.

Images