Research on Obstacle Avoidance Planning of Serpentine Manipulator Based on Particle Swarm Optimization

Compared with traditional manipulators, serpentine manipulator have the advantage of high flexibility and have broad prospects in exploring confined spaces. Aiming at the problems of large amount of calculation and poor obstacle avoidance effect in motion planning of serpentine arm in complex space environment. In this paper, combined with the particle swarm algorithm, a "head traction" path tracking method is designed, so that the rope-driven serpentine manipulator can efficiently move along the planned path in complex terrain. In the method of this paper, the obstacle modeling is completed first, and then a serpentine arm path planning algorithm based on particle swarm optimization is further designed. Use the planned path as the path point tracked by the serpentine manipulator "head". As the manipulator moves forward, all joints follow the path traveled by the manipulator's "head". In the final stage, in order to ensure that the manipulator can accurately reach the target point, an end position adjustment algorithm is designed. Through the simulation experiment of the rope-driven serpentine manipulator based on 21 degrees of freedom, it is proved that the method can successfully make the serpentine manipulator move in complex space, and has high computational efficiency and high precision, which is well verified the validity of the study.