Stable grasping under pose uncertainty using tactile feedback
This paper deals with the problem of stable grasping under pose uncertainty. Our method utilizes tactile sensing data to estimate grasp stability and make necessary hand adjustments after an initial grasp is established. We first discuss a learning approach to estimating grasp stability based on tactile sensing data. This estimator can be used as an indicator to the stability of the current grasp during a grasping procedure. We then present a tactile experience based hand adjustment algorithm to synthesize a hand adjustment and optimize the hand pose to achieve a stable grasp. Experiments show that our method improves the grasping performance under pose uncertainty.
grasping uncertainty tactile sensing robustness