Mobile robot narrow channel passing method based on Voronoi diagram
By adopting a Voronoi graph-based path planning method in mobile robots, combining heuristic search and Pure Pursuit algorithm, the problem of unstable and inaccessible paths in narrow environments is solved, and efficient and safe pass effect is achieved.
Patent Information
- Application Number
- CN202411988699.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-31
- Publication Date
- 2025-04-11
AI Technical Summary
When mobile robots need to pass through areas with dense obstacles and narrow spaces, traditional path planning algorithms are prone to fall into local optimal solutions, resulting in path unstable or feasible paths being impossible to plan.
The over-narrow channel method of mobile robots based on Voronoi graph is adopted to build local grid maps, generate Voronoi skeleton maps, and combine heuristic search algorithms and Pure Pursuit algorithms for path planning and tracking navigation.
It realizes efficient and safe passage of robots in narrow environments, can find the optimal or approximately optimal collision-free path, and has high flexibility and adaptability.
Smart Images
Figure CN119806156A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of robots, and in particular to a method for a mobile robot to pass through a narrow channel based on a Voronoi diagram. Background Art
[0002] In complex and ever-changing environments, mobile robots face severe path planning challenges, especially when they need to pass through areas with dense obstacles and narrow spaces, such as narrow passages or gates. These scenarios not only require robots to have high flexibility, but also require their path planning algorithms to ensure efficient and safe passage in limited spaces. Traditional path planning algorithms, although they perform well in open areas, often fail to cope with small spaces. They are prone to falling into local optimal solutions, resulting in unstable paths, and even the risk of colliding with obstacles, or simply being unable to plan a feasible path.
[0003] As a geometric construction method, the Voronoi diagram can generate a series of skeleton paths that are farthest from obstacles in a given space. These paths provide a potential solution for the navigation of mobile robots in narrow environments. This feature of the Voronoi diagram enables it to naturally avoid obstacles, thereby theoretically improving the efficiency and safety of passage. However, despite the many advantages of the Voronoi diagram, existing technologies have failed to fully combine it with dynamic obstacle avoidance algorithms to further optimize the robot's performance in complex environments. Summary of the invention
[0004] In view of the deficiencies in the prior art, the present invention discloses a method for a mobile robot to pass through a narrow channel based on a Voronoi diagram to solve the problems raised in the above background technology.
[0005] To achieve the above object, the present invention provides the following technical solution: a method for a mobile robot to pass through a narrow channel based on a Voronoi diagram, comprising the following steps:
[0006] S1. Construct a local grid map based on the current environment to provide a basis for positioning and planning;
[0007] S2, constructing a Voronoi skeleton diagram based on the constructed local grid map;
[0008] S3, using heuristic search algorithm for global path planning;
[0009] S4, using the Pure Pursuit algorithm for local path tracking navigation to complete the passage through the narrow channel.
[0010] Preferably, in step S1, the specific steps of constructing the local grid map include:
[0011] 1) After the robot is started, it determines the current position information through its positioning algorithm, and generates navigation instructions in combination with the global path planning module to drive the robot to move to the target narrow channel entry point;
[0012] 2) After reaching the entrance of the narrow channel, the system begins to build a grid map of the local environment; it uses the installed lidar and depth camera to collect point cloud data around the narrow channel, converts it into a two-dimensional grid map, and then completes the construction of the local grid map of the environment; wherein, each grid represents a spatial unit of a fixed size and is marked as "passable" or "obstacle" according to the sensor detection results; the local grid map has lower computational overhead than the global map, and can more accurately reflect the real-time environmental information around the narrow channel; it lays an accurate and reliable foundation for the subsequent conversion into a Voronoi skeleton map.
[0013] Preferably, when the robot drives towards the entry point of the narrow channel, the robot adjusts the travel path in real time through an obstacle avoidance algorithm to ensure that dynamic obstacles or inaccessible areas in the environment are avoided.
[0014] Preferably, in step S2, the specific steps of constructing the Voronoi skeleton diagram include:
[0015] 1) Construct a Delaunay triangular mesh
[0016] The Delaunay triangulation algorithm is used to grid model the passable area in the constructed local grid map. First, the boundary points of the passable area in the local grid map are extracted as the input of the Delaunay triangulation. Then, the Delaunay algorithm is used to generate a set of triangular meshes that meet the conditions. The vertex of each triangle is a key point in the environment. Through the triangular mesh map, a more abstract description of the environment can be made, which is convenient for the subsequent generation of the path skeleton.
[0017] 2) Dual Voronoi diagram construction
[0018] Based on the Delaunay triangulation result, the corresponding dual Voronoi diagram is constructed; the Voronoi diagram is a segmentation method based on spatial points, which is used to divide the influence range of each point in the environment; for each Delaunay triangle, the center of its circumscribed circle is taken as the vertex of the Voronoi diagram; by connecting the above vertices, a series of Voronoi edges are formed to form a complete Voronoi diagram;
[0019] 3) Construct Voronoi skeleton diagram
[0020] On the basis of the Voronoi diagram, the skeleton path formed by the center line of the environment is further extracted, which can provide the best passing path between obstacles in narrow channels and lay the foundation for the subsequent path planning algorithm; first, the redundant edges adjacent to obstacles or inaccessible areas in the Voronoi diagram are removed, and then the main path connecting the entrance and exit is retained to form a simplified skeleton diagram.
[0021] Preferably, in step S3, a heuristic search algorithm is used for global path planning, and the specific steps include:
[0022] 1) Convert the vertices and edges of the Voronoi skeleton graph into a graph structure, where each vertex represents a position and each edge represents the travel cost between adjacent vertices;
[0023] 2) Set the narrow channel entrance as the starting point and the exit as the target point, perform path search through the A* algorithm or Dijkstra algorithm, and output the optimal planned path, which is based on the edges in the skeleton graph and avoids obstacles to the greatest extent.
[0024] Preferably, in step S4, the Pure Pursuit algorithm is used to perform local path tracking navigation to complete passing through the narrow channel. The specific steps include:
[0025] After obtaining the optimal path, the robot uses the Pure Pursuit algorithm to track the path. During the path tracking process, the system updates the relative position of the robot and the preview point in real time, and dynamically adjusts the motion control instructions to ensure that the robot always travels along the optimal path and finally drives to the exit point of the narrow channel to complete the passage of the narrow channel.
[0026] Compared with the prior art, the present invention has the following beneficial effects:
[0027] 1. In the present invention, the Voronoi diagram is used to generate a skeleton path farthest from obstacles in space, and a dynamic obstacle avoidance algorithm is combined to achieve efficient and safe passage of the robot in a narrow environment.
[0028] 2. In the present invention, by constructing a Voronoi diagram and using a heuristic search algorithm for path planning, an optimal or approximately optimal collision-free path can be found for the robot.
[0029] 3. The present invention has high flexibility and adaptability and can cope with obstacles of different shapes and sizes as well as complex narrow channel environments. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.
[0031] In the attached picture:
[0032] Figure 1 It is a schematic diagram of the structure of the narrow channel environment of the present invention;
[0033] Figure 2 It is a schematic diagram of the process of the mobile robot passing through a narrow channel of the present invention;
[0034] Numbers in the figure: 101, mobile robot; 102, obstacle; 103, local grid map; 104, entry point; 105, exit point. DETAILED DESCRIPTION
[0035] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.
[0036] Example:
[0037] like Figure 1 As shown, the mobile robot 101 includes various environmental perception sensors, which can collect external environmental information and construct an environmental map. The mobile robot 101 first moves to the position of the entry point 104, and then constructs a local grid map 103 through the coordinates of the obstacle 102 in the target point cloud data scanned by the SLAM algorithm and the laser radar, providing a basis for path planning, so that it can navigate to the exit point 105.
[0038] like Figure 2 As shown, the present invention provides a method for a mobile robot to pass through a narrow channel based on a Voronoi diagram, which uses the Voronoi diagram to generate a skeleton path farthest from obstacles in space, and combines a dynamic obstacle avoidance algorithm to achieve efficient and safe passage of the robot in a narrow environment; the specific steps are as follows:
[0039] (1) Navigate to the narrow channel entry point 104
[0040] After the mobile robot 101 is started, the current position information is determined by its positioning algorithm, and the navigation instructions are generated in combination with the global path planning module to drive the mobile robot 101 to move to the target narrow channel entry point 104. During this process, the mobile robot 101 adjusts the travel path in real time through the obstacle avoidance algorithm to ensure that it avoids dynamic obstacles 102 or inaccessible areas in the environment.
[0041] (2) Constructing a local grid map of the environment 103
[0042] After reaching the entrance of the narrow channel, the system starts to build a grid map of the local environment. The point cloud data around the narrow channel is collected using a lidar and a depth camera and converted into a two-dimensional grid map. Each grid represents a fixed-size spatial unit and is marked as "passable" or "obstacle" based on the sensor detection results. The local grid map 103 has lower computational overhead than the global map and can more accurately reflect the real-time environmental information around the narrow channel. This lays an accurate and reliable foundation for the subsequent conversion to a Voronoi skeleton diagram.
[0043] (3) Constructing Delaunay triangular mesh
[0044] The Delaunay triangulation algorithm is used to mesh the passable area in the constructed local grid map 103. First, the boundary points of the passable area in the local grid map 103 are extracted as the input of the Delaunay triangulation. Then, a set of triangular meshes that meet the conditions are generated using the Delaunay algorithm, and the vertices of each triangle are key points in the environment. Through the triangular mesh graph, a more abstract description of the environment can be made, which is convenient for the subsequent generation of the path skeleton.
[0045] (4) Dual Voronoi diagram construction
[0046] Based on the Delaunay triangulation result, the corresponding dual Voronoi diagram is constructed. The Voronoi diagram is a segmentation method based on spatial points, which is used to divide the influence range of each point in the environment. For each Delaunay triangle, the center of its circumscribed circle is taken as the vertex of the Voronoi diagram. By connecting these vertices, Voronoi edges are formed to form a complete Voronoi diagram.
[0047] (5) Constructing the Voronoi skeleton diagram
[0048] Based on the Voronoi diagram, the skeleton path formed by the center line of the environment is further extracted, which can provide the best passing path between obstacles 102 in the narrow channel, laying the foundation for the subsequent path planning algorithm. First, the redundant edges adjacent to obstacles 102 or inaccessible areas in the Voronoi diagram are removed. Secondly, the main path connecting the entrance and exit is retained to form a simplified skeleton diagram.
[0049] (6) Use A* algorithm or Dijkstra algorithm to search for the optimal path
[0050] The vertices and edges of the Voronoi skeleton graph are converted into a graph structure, where each vertex represents a position and each edge represents the travel cost between adjacent vertices. The narrow channel entrance is set as the starting point and the exit is set as the target point, and the A* algorithm or Dijkstra algorithm is used for path search. The optimal path planned is output, which is based on the edges in the skeleton graph and avoids obstacles to the greatest extent 102.
[0051] (7) Use the PP algorithm to perform local path tracking and navigation to the narrow channel exit point 105
[0052] After obtaining the optimal path, the mobile robot 101 uses the Pure Pursuit (PP) algorithm to track the path. During the path tracking process, the system updates the relative position of the mobile robot 101 and the preview point in real time, and dynamically adjusts the motion control instructions to ensure that the mobile robot 101 always drives along the optimal path, and finally drives to the narrow channel exit point 105 to complete the narrow channel passing.
[0053] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A method for a mobile robot to pass through a narrow channel based on a Voronoi diagram, characterized in that: The following steps are involved: S1. Construct a local grid map based on the current environment to provide a basis for positioning and planning; S2, constructing a Voronoi skeleton diagram based on the constructed local grid map; S3, using heuristic search algorithm for global path planning; S4, using the Pure Pursuit algorithm for local path tracking navigation to complete the narrow channel.
2. The method for a mobile robot passing through a narrow channel based on a Voronoi diagram according to claim 1, characterized in that: In step S1, the specific steps of constructing a local grid map include: 1) After the robot is started, it determines the current position information through its positioning algorithm, and generates navigation instructions in combination with the global path planning module to drive the robot to move to the target narrow channel entry point; 2) After reaching the entrance of the narrow channel, the system begins to build a grid map of the local environment; it uses the installed lidar and depth camera to collect point cloud data around the narrow channel, converts it into a two-dimensional grid map, and then completes the construction of the local grid map of the environment; each grid represents a spatial unit of a fixed size and is marked as passable or an obstacle based on the sensor detection results.
3. The method for a mobile robot passing through a narrow channel based on a Voronoi diagram according to claim 2, characterized in that: When the robot drives toward the narrow channel entry point, the robot adjusts the travel path in real time through an obstacle avoidance algorithm to ensure that it avoids dynamic obstacles or inaccessible areas in the environment.
4. The method for a mobile robot passing through a narrow channel based on a Voronoi diagram according to claim 3 is characterized in that: In step S2, the specific steps of constructing the Voronoi skeleton diagram include: 1) Construct a Delaunay triangular mesh The Delaunay triangulation algorithm is used to grid model the passable area in the constructed local grid map. First, the boundary points of the passable area in the local grid map are extracted as the input of the Delaunay triangulation. Then, the Delaunay algorithm is used to generate a set of triangular meshes that meet the conditions, and the vertices of each triangle are key points in the environment. 2) Dual Voronoi diagram construction Based on the Delaunay triangulation result, construct the corresponding dual Voronoi diagram; for each Delaunay triangle, take the center of its circumscribed circle as the vertex of the Voronoi diagram; connect the above vertices to form Voronoi edges and form a complete Voronoi diagram; 3) Construct Voronoi skeleton diagram Based on the Voronoi diagram, the skeleton path formed by the center line of the environment is further extracted to provide the best passing path between obstacles in narrow channels; first, the redundant edges adjacent to obstacles or inaccessible areas in the Voronoi diagram are removed, and then the main path connecting the entrance and exit is retained to form a simplified skeleton diagram.
5. The method for a mobile robot passing through a narrow channel based on a Voronoi diagram according to claim 4, characterized in that: In step S3, a heuristic search algorithm is used to perform global path planning, and the specific steps include: 1) Convert the vertices and edges of the Voronoi skeleton graph into a graph structure, where each vertex represents a position and each edge represents the travel cost between adjacent vertices; 2) Set the narrow channel entrance as the starting point and the exit as the target point, perform path search through the A* algorithm or Dijkstra algorithm, and output the optimal planned path, which is based on the edges in the skeleton graph and avoids obstacles to the greatest extent.
6. The method for a mobile robot passing through a narrow channel based on a Voronoi diagram according to claim 5, characterized in that: In step S4, the Pure Pursuit algorithm is used to perform local path tracking navigation to complete the narrow passage. The specific steps include: After obtaining the optimal path, the robot uses the Pure Pursuit algorithm to track the path. During the path tracking process, the system updates the relative position of the robot and the preview point in real time, and dynamically adjusts the motion control instructions to ensure that the robot always travels along the optimal path and finally drives to the exit point of the narrow channel to complete the passage of the narrow channel.