一种改进的双向快速搜索随机树算法

An Improved Bidirectional Rapid-exploring Random Tree Algorithm

针对快速搜索随机树(RRT)算法随机性大、效率低的问题,提出了一种改进的双向RRT算法。该算法采用预生长机制,快速通过前期无障碍区域;以重要程度划分障碍物,减小势场计算规模,提高路径规划的避障效率;同时采用基于欧氏距离的筛选机制对随机点进行遴选,减少在低可能路径区域的生长。最后在仿真环境下进行实验,验证了所提算法的可行性和有效性。

An improved bidirectional rapid-exploring random tree(RRT) algorithm was proposed to solve the problem of high randomness and low efficiency of RRT. The algorithm adopted the pre-growth method to pass the barrier free area at the beginning quickly. In order to reduce the calculation scale and improve the obstacle avoidance ability, obstacles were divided by the level of importance. At the same time, a screening mechanism based on Euclidean distance was used to select random points, which could help to reduce the extended probability in the areas away from expected path. In the end, the feasibility and validity of the proposed algorithm were verified in the simulation experiments.