Towards Automated Self-Calibration of Robot Skin

This paper deals with the problem of calibrating a large number of tactile elements (i.e., taxels) organized in a skin sensor system after fixing them to a robot body part. This problem has not received much attention in literature because of the lack of large-scale skin sensor systems. The proposed approach is based on a controlled compliance motion with respect to external objects whose pose is known, which allows a robot to determine the location of its own taxels. The major contribution of this work is the formulation of the skin calibration problem as a maximum-likelihood mapping problem in a 6D space, where both the position and the orientation of each taxel are recovered. An effective calibration process is envisaged that, given a compliance control law that assures prolonged contact maintainance between a given body part and an external object, returns a maximum-likelihood estimate of detected taxel poses. Simulations validate the approach.