Redundancy optimization for mechanical manipulators

Redundant manipulators have some advantages when compared with classical arms because they allow the trajectory optimization, both on the free space and in the presence of obstacles, and the resolution of singularities. For this type of manipulators, the proposed kinematic control algorithms adopt generalized inverse matrices. The generalized inverse control scheme is tested through several experiments which reveal the difficulties that often arise, namely by showing that we may get non-optimal arm configurations and chaotic-like motions. Motivated by these problems we present a new method that optimizes the manipulability through a least square polynomial approximation to determine the joints positions. The experiments confirm the superior performance of the proposed algorithm for redundant and hyper-redundant manipulators.