传统的RRT(Rapid-exploration Random Tree)算法具有搜索速度快,适用于解决动力学非完整性约束问题,但是由于算法本身的随机性,生成的路径比较曲折,甚至出现绕远路现象.为此,本文提出一种改进的RRT路径规划算法,该算法结合目标偏向策略,使算法快速向目标节点收敛;对选取节点的度量函数,加入了角度的影响;同时引入贪心剪枝思想,对冗余节点进行剪枝,提高了路径规划算法的效率;最后通过仿真实验,验证了该算法的正确性和有效性.
摘要(英文)：
The traditional Rapid-exploration Random Tree algorithm has an excellence searching rate, the algorithm is suitable for solving the dynamics of nonholonomic constraint problems, but due to the randomness of the algorithm, the generated path is comparatively zigzagging, it usually results in tromboning. Therefore, this paper proposes an improved RRT path planning algorithm, combining with the target bias strategy, which makes the algorithm fast convergence to the target node;The metric function of selecting nodes increase the impact of angle;Meanwhile, it introduces an greedy pruning ideology t...
