We describe an algorithm that can robustly decide whether a grip or a footstep is secure given data collected from at least two independent sensors. This algorithm is based on the observation that if there is an absence of slip, then, owing to the high velocity of mechanical waves in solids, the two sensor signals must be highly correlated, even in the presence of internal or external perturbations. The statistical distance between signals collected during slip and non-slip phases, regarded as random distributions, also provides a continuous measure of graspability or walkability of an object being held or a ground being stepped on. We tested the algorithm on a bench using micro-electro-mechanical system (MEMS) accelerometers and with a variety of materials of different surface roughnesses. We also discuss the applications of this non-slip/slip discrimination algorithm and its putative relationship with human gripping behavior.
