Kinematic optimization of redundant and hyper-redundant robot trajectories

Redundant manipulators have some advantages when compared with classical arms because they allow a trajectory optimization, both on the free space and on the presence of obstacles, and the resolution of singularities. For this type of manipulators, the proposed kinematic control algorithms adopts generalized inverse matrices. In this line of thought, the generalized inverse scheme is tested through several experiments that 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 this paper presents a new method that optimizes the manipulability through a least square polynomial approximation to determine some joints positions. The experiments confirm the superior performance of the proposed algorithm for redundant and hyper-redundant manipulators.