Research on Motion Planning Method for Robotic Arm Under Obstacles

To solve the problem of the motion planning algorithm of a robotic arm, such as long search time, uneven planning path and large mechanical vibration during movement, this paper proposes a motion planning method for a robotic arm under obstacles. First, an improved Informed-RRT* algorithm is proposed for path planning. Based on the traditional Informed-RRT* algorithm, the bidirectional search strategy is introduced to reduce the randomness of search and improve the sampling efficiency. In the path growth stage, the adaptive step size strategy is adopted and the step size is dynamically adjusted according to the expanding trend of the search tree, so the local optimization can be avoid and the path search time can be reduced. Second, the 3-5-3 segmented polynomial interpolation method is used in trajectory planning. The purpose is to smooth the path and optimize the motion trajectory. Thus, the angular velocity of each joint of the manipulator is smooth and continuous, and the impact of the manipulator movement is reduced. In the experiment, the improved Informed-RRT* algorithm is compared with the traditional algorithm under the obstacle environment. The experiment results show that, compared with traditional path planning algorithms, the proposed method has shorter path length, fewer path branches and faster computation time. Compared with the traditional trajectory planning algorithm, the proposed method has faster response speed and smaller mechanical vibration.