Dynamic path planning method based on Hybrid-astar
A dynamic path and path technology, applied in road network navigators, measuring devices, instruments, etc., can solve the problems of not being able to meet the user's individual needs, not being able to avoid dynamic obstacles, and taking a long time
Pending Publication Date: 2021-06-08
GUANGZHOU HAIGE COMM GRP INC +1
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Problems solved by technology
It takes a long time to do long-distance or dynamic driving planning, and cannot avoid dynamic obstacles; and the hybrid A* algorithm is only suitable for approximate optimal path planning, and cannot meet the user's individual needs, so it is not suitable for dynamic paths planning
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[0066] The present invention will be further described below in conjunction with drawings and embodiments.
[0067] see figure 2 , one A dynamic path planning method based on Hybrid-astar, including:
[0068] S1, according to the known global path and the maximum path planning length d set by the user max and variable planning distance d plan Carry out granular segmentation of variable planning distances to generate a global path; the segmentation granularity can be flexibly set according to actual needs such as vehicle maneuverability and road conditions to meet different application scenarios. Specifically, step S1 includes, according to the current position of the vehicle, in the global path set Ψ={p 1 ,p 2 ,...,p n} to find the nearest point P to the vehicle nearest , the point P closest to the vehicle nearest As a starting point for planning and added to the path subset middle;
[0069] Traverse the global path set Ψ point by point from the starting point, an...
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The invention discloses a dynamic path planning method based on Hybrid-astar, which comprises the following steps of: S1, performing granularity segmentation of a variable planning distance according to a known global path, a maximum path planning length dmax set by a user and the variable planning distance dplan to generate a global path; S2, optimizing the dynamic path, wherein the step of optimizing the dynamic path comprises the substep of planning at least one of multi-point combination path search, angle smoothing and Bezier curve difference smoothing in a subsection manner; and S3, periodically issuing the optimized path to the unmanned vehicle, wherein the unmanned vehicle runs according to the path. According to the invention, the granularity segmentation is performed according to a variable planning distance to generate a global path, and the global path is decomposed into a plurality of path point subsets; the multi-point combined path searching method is adopted for path searching, and the success probability of path searching is improved.
Description
technical field [0001] The invention relates to the technical field of vehicle dynamic path planning, in particular to a hybrid-astar-based dynamic path planning method. Background technique [0002] Hybrid A* algorithm is often used in path planning. Hybrid A* (Hybrid-astar) is a global and static path planning algorithm. The motion trajectory is generated by heuristic search in the continuous coordinate system, and the vehicle non-integrity constraint is performed on the motion trajectory to obtain the final motion trajectory of the vehicle. The traditional A* algorithm uses 2D Euclidean distance heuristic search, hybrid A* uses vehicle non-integrity constraint heuristic search and integrity constraint heuristic search, and uses Reeds-Shepp curve to speed up the search. see figure 1 , the implementation steps of the hybrid A* algorithm are: [0003] 1) Add the starting point to the open list; [0004] 2) Repeat the following steps to traverse all nodes: [0005] ① Tra...
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IPC IPC(8): G01C21/34
CPCG01C21/3415
Inventor 钟英杰盛书磊
Owner GUANGZHOU HAIGE COMM GRP INC