A path planning algorithm for unmanned vehicles based on target-oriented rapidly-exploring random tree
Haijun Gong, Chenkun Yin, Fang Zhang, Zhongsheng Hou, Ruikun Zhang · 2017
A path planning algorithm for the unmanned vehicles based on target-oriented rapidly-exploring random tree (RRT) is proposed in this paper with the objective of improving search efficiency for the basic RRT algorithm. According to the idea of target-oriented search, the information of the target node is always utilized for the global search which makes the algorithm directional and fast. In the vicinity of the obstacle, the local path planning is carried out by using the optimized RRT algorithm to meet safety requirements of the vehicle. With the help of a heuristic function for node evaluation, the random tree generated is pruned and optimized with fewer search nodes in a shorter distance. The B-spline curve is used for fitting the nodes to derive a smooth feasible path such that the kinematic constraints of vehicle are taken into consideration. The effectiveness and advantages of the proposed algorithm are verified by simulation and road experiment.