针对Informed-RRT*算法在路径规划中与动态障碍物的碰撞问题, 提出基于Informed-RRT*和人工势场法的改进路径规划算法。该算法引入椭圆区域采样策略和自适应步长策略提高了寻找可行全局路径的稳定性和效率, 在静态障碍物边界区域获得最优成本可行路径方案。当机器人按照全局路径运动遇到动态障碍物时, 引入裁剪路径分支策略和人工势场法对局部路径进行重规划, 实现动态避障功能。将改进算法应用于仿真环境, 结果表明改进算法实现了全局最优探索和局部避障功能, 验证了算法的有效性。

Regarding the problem of the Informed-RRT* algorithm of collision with dynamic obstacles in path planning, an improved path planning algorithm based on Informed-RRT* and artificial potential field method is proposed.The algorithm introduces elliptical region sampling strategy and adaptive step-size strategy to improve the stability and efficiency of finding feasible global path, and the optimal cost feasible path scheme is obtained in the boundary region of static obstacles.When the robot encounters dynamic obstacles in its movement according to the global path, the cutting path branching strategy and artificial potential field method are introduced to re-plan the local path to realize dynamic obstacle avoidance.The improved algorithm is applied to the simulation environment, and the results show that the improved algorithm achieves the functions of global optimal search and local obstacle avoidance, which verifies the effectiveness of the algorithm.