Variable probability bidirectional rapidly-exploring random tree improved path planning algorithm

Abstract

The invention relates to a variable probability bidirectional rapidly-exploring random tree improved path planning algorithm. Firstly, when importing a state space map, state space preprocessing needsto be performed according to the setting of the vehicle volume, and the state space edge is extended and protected to prevent the node from excessively approaching the state space edge to cause a collision. Secondly, a variable probability target selection strategy based on the node environment is adopted to accelerate the convergence speed. Finally, the bent part in the generated path is removedwhile the straight part in the generated path is retained, that is, whether connection lines between the first node as the start and the subsequent nodes have an obstacle is judged, the redundant nodes are deleted, the path is optimized, and the number of turns and the total path length during the driving of the trolley are reduced. The variable probability optimization algorithm is achieved based on the original bidirectional RRT algorithm, and the target pointing method is used to improve the search speed and reduce the calculation amount. At the same time, the path length and the number ofnodes are reduced, and the passability is ensured.

Description

technical field [0001] The invention relates to a path planning technology for an intelligent vehicle, in particular to an improved path planning algorithm of variable probability bidirectional fast search random tree. Background technique [0002] Smart car path planning means that the smart car finds a continuous collision-free path from the initial pose point to the target pose point in the pose space. At the same time, this path must meet the environmental constraints and the motion characteristics of the smart car itself. [0003] In response to this situation, people proposed the RRT (Rapid Search Random Tree) algorithm. The core of the algorithm is a random search method, which can realize path search in high-dimensional non-convex spaces. Because it uses random sampling planning, no preprocessing is required, and the search The speed is fast, and the speed advantage is especially obvious in high-dimensional space. In recent years, it has been widely used and research...

AI Technical Summary

Problems solved by technology

[0004] The present invention is aimed at solving the existing problems of robot motion planning with the fast search random tree algorithm, and proposes a variable probability bidirectional fast search random tree improved path planning algorithm, which ensures the accessibility under the search speed

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