AN OPTIMAL ADMITTANCE REACTIVE FORCE CONTROL FOR COOPERATIVE ROBOT GRASPING TASKS

Abstract

In this article it is proposed an optimal admittance algorithm that controls the position of the end effectors in cooperative robot systems or fingers, in case of robotic hands, reactively according to on-line force sensory data. The method is free of in-depth models or sophisticated external sensors. The sensors used are simple and provide only limited and immediate information, nonetheless they allow to reactively correct the applied force to guarantee object stable grasp. Force sensory information is used to determine modification of the desired movement of the robots at a cooperative system, so that ultimately the applied force to guarantee a stable object grasp is achieved. The proposed optimization algorithm uses force error at each robot as a correction factor when calculating a modified Cartesian desired trajectory, thus it results on real time reactive motion planning. The novelty of the proposed algorithm is that the adaptive admittance controller is obtained as the solution of a dynamic optimization problem which is solved via the standard gradient flow approach. The proposed methodology considers grasps and fixtures whose contacts react according to force displacement laws consistent with friction constraints at the contact points. It is only assumed that each robot end effector is capable of generating its own linear force displacement. Experimental results show that the proposed controller is robust against environmental stiffness uncertainties and its variations, as well as object position uncertainty, as far as an initial contact between the robots and the object is guaranteed.