Obstacle avoidance path planning of space manipulator based on improved RRT algorithm

The traditional rapid expansion random tree (RRT) algorithm has poor efficiency in the motion planning of the manipulator. Based on the traditional RRT algorithm, this paper introduces the target offset strategy in the process of expanding leaf nodes. When the algorithm falls into a local minimum, it will select the expansion point, so as to quickly break away from the minimum. The improved RRT algorithm and other algorithms are simulated in Mathematica. The experimental results show that the improved algorithm can guide the growth direction of the tree, improve the convergence speed of the algorithm, make it difficult to fall into local minimum, and improve the motion planning efficiency of the manipulator in simulation.