A Topological Approach to Globally-Optimal Redundancy Resolution with Dynamic Programming

Redundancy resolution schemes based on calculus of variations present several drawbacks limiting the intrinsic potential, in terms of augmented dexterity and flexibility, of redundant manipulators. In particular, they do not guarantee the achievement of the globally-optimal solution. Grid search algorithms can be designed starting from dynamic programming (DP) which overcome the limits of calculus of variations. This paper, in particular, presents a novel algorithm that considers the employment of multiple DP grids to be searched together at the same time. Such a technique achieves the global optimum, while allowing for pose reconfiguration of the manipulator while the task is executed.