A global cartesian space obstacle avoidance scheme for redundant manipulators

Abstract

Abstract Optimal control of kinematically redundant manipulators involves the use of extra degrees of freedom to improve their performance by energy minimization, singularity avoidance, obstacle avoidance, higher dexterity, etc. In this paper we deal with the obstacle avoidance problem by using modern control theory and choosing an integral‐type performance index which results in a global optimization scheme. Obstacles are expressed as Cartesian space constraints. The state constraint function and control effort are minimized globally as a performance index. The control effort which maximizes the Hamiltonian and minimizes the performance index is used to find the self‐motion of the manipulator. A simulation for a three‐degrees‐of‐freedom redundant planar robot is presented to demonstrate the effectiveness of the scheme.