Robots are increasingly used to perform complex tasks, which often involve interaction and contact with unstructured environments. By identifying geometric uncertainties and the dynamic behavior of the environment on-line, the autonomy of intelligent robot systems can be considerably improved. This paper considers the 2D case of an industrial robot equipped with a probe to explore an unknown environment. The goal is to estimate from the measured end-effector position, velocity and forces not only the environmental contact dynamics parameters, but also geometric parameters such as the environment position and orientation, and the position of the probe end-point with respect to the robot end-effector. To this end, a Kalman filter based algorithm is proposed, which enforces physical constraints and which is executed in an event-triggered way to improve convergence and robustness. Experimental results illustrate the viability of the proposed algorithm.
['D. Verscheure', 'Jan Swevers', 'Herman Bruyninckx', 'Joris De Schutter']
On-line identification of contact dynamics in the presence of geometric uncertainties