Simultaneously obstacle avoidance and kinematic control for redundant manipulators based on improve danger field

Abstract

Redundant robots are widely used because of their superior flexibility. However, due to the physical constraints and the influence of uncertain obstacles in the workspace, it brings great challenges to the high-precision kinematic control of redundant robots. This paper presents a real-time obstacle avoidance and high-precision kinematic control method for redundant robot based on improved danger field method. An improved danger field description is established to improve the adaptability of the system to dynamic obstacles by introducing the speed forward-looking information between robot and obstacles. The kinematic control strategy with finite time convergence is designed. The dynamic programming type problem description is established through two terminal inequality constraint modeling of joint angle and velocity. Then a recursive solver is designed to solve the nonlinear HJB problem, and the control command is obtained in real time. The stability of the closed-loop system is analyzed. Simulation results show that the proposed method has better obstacle avoidance performance than traditional dangerous field, and has better advantages in avoiding physical constraints.