On the Variability of Tactile Signals During Grasping

Robotic manipulation in unstructured environments must handle a wide range of objects despite errors in visual perception. Tactile sensing is presumed to provide essential information in this context, but there has been little work examining the tactile sensor signals produced during realistic manipulation tasks. This paper presents tactile sensor data from grasping a generic object in hundreds of trials. Position error between the hand and object was varied to model the uncertainty in real-world grasping. Results show that tactile signals are highly variable despite good repeatability in grasping conditions. The observed variability appears to be intrinsic to the grasping process, due to the mechanical coupling between fingers as they contact the object in parallel, and due to numerous factors such as frictional effects and inaccuracies in the robot hand. These results have implications for improved tactile sensor system design and signal processing methods.