Measuring contact points from displacements with a compliant, articulated robot hand

Manipulators with compliant actuation exhibit passive joint displacements when exposed to external forces or collisions. This paper demonstrates that this displacement information is sufficient to infer a coarse estimate of the location of an incidental collision. Three techniques for contact point detection are compared: a closed-form inference model based on a serial chain with joint springs, a variation on Self Posture Changeability, and an empirical memory-based model of joint trajectories. The methods were experimentally tested using a Shadow Hand on an industrial Motoman SDA10 arm to quantify localization performance, actively discover and avoid a thin obstacle and localize and grasp a cup.