Pareto Optimality and Multiobjective Trajectory Planning for a 7-DOF Redundant Manipulator

This paper presents a novel approach to solve multiobjective robotic trajectory planning problems. It proposes to find the Pareto optimal set, rather than a single solution usually obtained through scalarization, e.g., weighting the objective functions. Using the trajectory planning problem for a redundant manipulator as part of a captive trajectory simulation system, the general discrete dynamic programming (DDP) approximation method presented in our previous work is shown to be a promising approach to obtain a close representation of the Pareto optimal set. When compared with the set obtained by varying the weights, the results confirm that the DDP approximation method can find approximate Pareto objective vectors, where the weighting method fails, and can generally provide a closer representation of the actual Pareto optimal set.