Multi-tactile sensor calibration via motion constraints with tactile measurements

This paper addresses a fundamental problem in multi-finger robot dexterous manipulation, Multi-Tactile Sensor Calibration (MTSC). It involves estimating the relative poses between multiple tactile sensors using their intrinsic measurements, crucial for coordinating multiple fingers in a dexterous robotic hand, especially when accurate encoders are unavailable. Unlike conventional multi-sensor calibration methods (like cameras), which rely on overlapping sensing regions and feature point matching, calibrating multiple tactile sensors presents unique challenges because these sensors cannot have overlapping sensing regions, precluding the use of shared key-points visible from different sensors. In this paper, we establish the theoretical basis for the MTSC problem, constructing constraint equations based on motions measured at multiple locations on the same grasped object from different tactile sensors. The key is that all these measurements correspond to a shared rigid body motion. A calibration scheme is proposed accordingly, with theoretical analysis conducted to enhance precision. Results in simulation, with objects of different shapes, confirm the validity of the proposed calibration approach. Furthermore, calibration of the relative pose between two GelSlim vision-based tactile sensors in real experiments demonstrates good agreement with the ground truth. The proposed theory and method not only shed light on explaining the accuracy gap between proprioception and tactile sensing in multi-finger manipulation but also pave the way for tactile-encoder-mixed or encoder-free solutions in dexterous multi-finger coordination.