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Robot multi-source shortest path planning method based on territorial limitation

A shortest path and area-limited technology, applied in the field of mobile robots, can solve the problems of difficult estimation of the time complexity of the A* algorithm, low efficiency of multi-source path planning, repeated calculations, etc., to improve computing efficiency, real-time performance, and high stability , Implement high-precision effects

Inactive Publication Date: 2018-10-02
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

The A* algorithm is a heuristic algorithm. It can usually quickly find the shortest path for a given starting point and end point. However, depending on the heuristic strategy and the actual environment, the time complexity of the A* algorithm is difficult to estimate, and For the multi-source shortest path problem, using the A* algorithm will cause a lot of repeated calculations
Overall, existing path planning methods are inefficient and complex for multi-source path planning

Method used

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  • Robot multi-source shortest path planning method based on territorial limitation
  • Robot multi-source shortest path planning method based on territorial limitation
  • Robot multi-source shortest path planning method based on territorial limitation

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Embodiment

[0041] Specific as figure 1 shown, including the following steps:

[0042] (1) Arrangement of vertices in the visual graph: according to the actual work needs of the robot, artificially set a number of different mobile nodes in the working area of ​​the robot in advance, and record the coordinates of each mobile node as the basis for this algorithm to find the shortest path, and ensure that the robot can By moving between the set mobile nodes to traverse the entire robot working route.

[0043] (2) Calculation of the connection weight between vertices: according to the coordinates of each mobile node, calculate the straight-line distance between any two mobile nodes, introduce the auxiliary vector D, and each component D[i][j] represents a certain mobile node v i to other mobile nodes v j The straight-line distance, where, if from v i to v j There is no traffic obstacle between them, then D[i][j] is v i to v j Straight-line distance, otherwise set D[i][j] to ∞. Thereby ...

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Abstract

The invention relates a robot multi-source shortest path planning method based on territorial limitation. The distance between moving nodes with connected edges is set to the weight of the weight of the connected edges and the distance between moving nodes without connected edges is set to be infinity, so connection information between moving nodes is obtained and abstract maps are constructed. Bycomparing the set formed by all departure points and all target points and the set of solved shortest path moving nodes, the undetermined shortest path top point set at the current moment is obtained. According to the top point coordinates and the confidence coefficient of the shortest path in current undetermined shortest path top point set, the extreme value of the top point coordinate in the top point set is obtained, and a rectangular limitation searching region including the including whole departure point and the target point set is constructed. The shortest path of the departure pointsand the target points with connection edges is the weight of the connection edge. For other departure points and target points, a Dijkstra algorithm is used for determining the shortest path. According to the invention, path planning can be simply, conveniently and highly efficiently achieved and stability is high.

Description

technical field [0001] The invention belongs to the technical field of mobile robots, and in particular relates to a robot multi-source shortest path planning method based on area restrictions. Background technique [0002] With the wide application of robots, smart cars and other equipment in life and production, people have higher and higher requirements for their intelligence, and finding the shortest path is the basic requirement and core technology of mobile robot path planning. Especially in indoor conditions with high precision requirements and complex motion environment, how to effectively determine the optimal path planning is an important and meaningful problem. [0003] At present, the relatively mature path planning methods mainly include Floyd algorithm, Dijkstra algorithm, Bellman-Ford algorithm and so on. Among them, the Floyd algorithm can calculate the shortest path between any two nodes, but the complexity of the algorithm is high. Both the Dijkstra algor...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0221G05D1/0276
Inventor 郭健宋恺刘源吴益飞李胜
Owner NANJING UNIV OF SCI & TECH
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