Immune optimization based multi-objective six-DOF trajectory planning for industrial robot manipulators

Abstract

Optimal trajectory planning for robot manipulators is always a hot spot in research fields of robotics. This paper presents a Constraint Immune Multi-objective Optimization Algorithm (CIMOA) for computing optimal trajectory of an industrial robot manipulator. The problem has a multi-criterion character in which two objectives, the minimum traveling time objective and minimum mechanical energy consumption objective are considered. In this paper, a model of trajectory planning for six-DOF manipulator based on CIMOA is established. With robot's mechanism system constraints, taking minimum traveling time and minimum energy as criterion, the robot trajectories are planned using CIMOA. Compared the results with single objective algorithm by genetic algorithm (GA) and weighted objective genetic algorithm (WGA), it is shown that, the travelling time and consuming energy by multiple objective method CIMOA are much less, and the trajectory in joint space is much smoother.