CETSP-based Trajectory Planning for Redundant Manipulators

The trajectory planning problem for redundant manipulators is studied, where the DOF (degree of freedom) of the manipulator is larger than 6. The end-effector is constrained to visit a series of task areas, similar to the Close-Enough Traveling Salesman Problem (CETSP). However, the multiple inverse solutions of redundant manipulators must be considered. This paper proposes an improved genetic algorithm with the simultaneous introduction of three different types of genes. Each chromosome contains three parts, including the order of task areas, the sequence of joint configurations, and the unknown coefficients to be optimized. Numerical simulations are carried out to validate the proposed method. The results show that the end-effector of redundant manipulator accurately visits all task areas.