Semi-autonomous control of excavation using model of human operation and state estimation via Extended Kalman Filter

Abstract

For robotic teleoperation, semi-autonomous control, i.e. autonomous control allowing human interposition will be an effective way overcoming delay of electrical communication and emergency operation. We have proposed semi-autonomous control method focusing on excavation in teleoperation environments. In the method, a model of human operation is designed and human internal state is estimated by Extended Kalman Filter. In this paper, experimental evaluations are conducted and reported about ”Digging” process. A human skill of excavation is modeled by an attractor-based dynamics embedding shallow and deep digging trajectories for soft and hard soil, respectively. An index parameter is changed based on the load of the bucket, and a seamless motion transition is realized satisfying the restriction by setting a threshold. Moreover, by adding a human operation to the autonomy, the proposed method will cope with the emergency, which is experimentally evaluated.