Aiming at the problems of the rapid search random tree(RRT)algorithm in the material trolley path planning algorithm,such as many turning points,long path length,and slow algorithm running speed,a research on the material trolley path planning algorithm based on improved RRT was carried out.This article first analyzes the principles,advantages and disadvantages of the RRT algorithm and the RRT-C algorithm.Then,it proposes a sampling optimization strategy for finding the optimization target point,a step size optimization strategy,and corner constraint conditions to ensure the safety of the material trolley.Finally,pruning optimization and rounded angle path smoothing strategies are used to optimize the path to match the actual running route of the material trolley,and the obstacles are expanded to avoid the problem of insufficient safety.The optimized RRT algorithm has an improvement of 40%～60%and 15%～30%in planning time and path length respectively compared with the initial method,which proves the effectiveness of this method.Research on the path planning of material trolleys in smart communities based on the improved RRT algorithm has important theoretical and application significance,and provides a basis for the optimization of dynamic logistics management systems in smart communities in the future.
关键词
路径规划/物料小车/快速搜索随机树算法/采样策略/剪枝优化/路径平滑
Key words
Path Planning/Material Trolley/Rapidly-exploring Random Trees Algorithm/Sampling Strategy/Pruning Optimization/Path Smoothing
维普
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