Obstacle avoidance path planning algorithm for mobile robot based on improved RRT

For traditional RRT* algorithm, It has long search time, low sampling efficiency, and the path is not smooth. To solve these problems, this paper presents an improved algorithm. First, the algorithm uses the strategy of selecting the target point as the sampling point with adaptive probability to guide the random tree to grow towards the target point and accelerate the convergence of the algorithm; Then, we pruned and smoothed the path to solve the problem of redundant and tortuous paths after planning. The simulation results show that compared with the traditional RRT* algorithm, the improved RRT* algorithm has less planning time, shorter road stiffness length and higher path quality.