Research on kinematics modeling and path planning of a hyper-redundant continuum robot

Abstract

It has always been the case that work in confined spaces has high difficulty and complexity, and robots are usually required to replace humans to perform the corresponding operations. For the maintenance work in the fuel tank of a certain type of aircraft, a continuum robot with 32 staggered orthogonal joints is designed in this paper. To solve the motion problem of this robot, this paper combines the end-following method with the Jacobi inverse kinematics method, and proposes an end-following-segmented Jacobi method, which improves the accuracy and efficiency of the inverse kinematics solution. A ray path-planning algorithm for continuum robots is proposed for the job requirements of this robot and the specific operating environment inside an airplane fuel tank, and it is compared with the rapidly-exploring random trees (RRT) algorithm and particle swarm optimization (PSO) algorithm. The experimental results show that the planning time of the ray path-planning algorithm is less compared with the RRT algorithm and the PSO algorithm, and the paths obtained are shorter. Finally, a path-following simulation is performed on a 32-joint continuum robot model to verify the followability of the ray path algorithm.