A Grasping Force Optimization Algorithm for Multiarm Robots With Multifingered Hands

The computation of the grasping forces for a multiarm robotic manipulation system (e.g., an anthropomorphic bimanual system) is considered in this paper. This problem is formulated as a convex optimization problem, also considering joint torque constraints. An algorithmic solution suitable for online implementation is presented, which allows a substantial reduction in the computational load by adopting a compact formulation and dynamically decreasing the number of active torque constrains. Moreover, for the case of a bimanual manipulation system, a suboptimal single-hand optimization algorithm is proposed and compared with that providing the optimal solution. Finally, a new algorithm for a valid initial-point evaluation is proposed. The effectiveness of the described methods has been tested in a simulation case study where the grasping forces of a humanoid torso equipped with two five-finger robotic hands are modified online to handle a load with a time-varying mass.