Neuroadaptive calibration of tactile sensors for robot skin

In this paper we present a novel automated neuroadaptive approach that can characterize pressure sensitive “skin” deployed on a robot. Both the safety and performance of future co-robots can be greatly enhanced by such sensorized skin, by measuring multiple contact forces with humans and the environment. A challenge that arises with robot skin is the task of calibration to achieve reliable measurements necessary for safe human-robot interaction. To this end, the traditional method of calibrating each sensor prior to its use is a tedious task, especially with inexpensive, miniaturized hardware that can experience material degradation with time. Therefore, we propose an adaptive strategy that learns the sensor array characteristics together with the unknown dynamics of both the robot and human during physical interaction. Convincing experimental results with deployed pressure skin sensors on a PR2 robot are presented to validate our approach.