A New Path Planning Method of Obstacle and Singularity Avoidance for Redundant Robot

Abstract

This thesis proposes a path planning method of obstacle and singularity avoidance with synergistic effect for redundant robot. By analyzing robot configuration, it proposes an improved method to calculate real-time minimum distance. At first, it screens out the connecting rod which might collide. Then, it calculates the distance by coordinate variation method and took the minimum value. At last, it obtains the real-time minimum distance. By introducing two obstacle avoidance parameters related to the real-time minimum distance, this thesis uses the self-motion of redundant kinematic chain in null space to complete obstacle avoidance. Also, it applies DLS method to complete singularity avoidance optimization to the obstacle avoidance algorithm. It solves the problem of excessive joint velocity close to singularity configuration. In the end, this thesis verifies the effectiveness of the algorithm by conducting simulation experiment on a plane 3R redundant robot.

Research on Lifting Path Planning Algorithms for Intelligent Cranes

“…Zhang et al [22] generate fan-shaped path effective area according to the actual operating area of the tower crane and reorder the first generation particles, which can effectively improve the efficiency of the tower crane operation and verify the feasibility of the algorithm. Li et al [23] sorted the particles according to the fitness value to improve the speed of the algorithm, and added the path length and path smoothness to the fitness function to make the generated path smoother. The feasibility of 3D environment was verified.…”