A Dynamic Programming Approach to Redundancy Resolution with Multiple Criteria

This paper studies the problem of generating optimal joint trajectories for redundant manipulators when multiple criteria need to be considered and proposes a novel approach based on dynamic programming and the use of the Pareto optimality condition. The drawbacks of the traditional weighting method in optimization for generating the Pareto optimal set are discussed and an alternate approach using dynamic programming is proposed. The two approaches are implemented on the model of a 7-DOF redundant manipulator with the end-effector moving along a prescribed trajectory, while the joint trajectories are required to minimize two particular criteria. The results illustrate that the dynamic programming approach provides a better approximation of the Pareto optimal set and a more flexible and predictable framework to control the objective vectors.