Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing

Abstract

A visual servoing control method based on depth point cloud is proposed to solve the problem of pose adjustment before obstacle surmounting of a rocker arm tracked robot. By pre-processing the acquired point cloud, a positional error model is created. Combined with the robot kinematics model, the adaptive control law is designed based on Lyapunov method, and the stability of the control algorithm is proved. Simulation results show that, compared with PID control and sliding mode control algorithm, the proposed control algorithm has faster convergence speed and smoother trajectory. The robot can reach the desired pose efficiently in 13. 5s in actual testing.