Robotics: Science and Systems XIV

Bayesian Tactile Exploration for Compliant Docking With Uncertain Shapes

Kris Hauser


This paper presents a Bayesian approach for active tactile exploration of a planar shape in the presence of both localization and shape uncertainty. The goal is to dock the robot's end-effector against the shape -- reaching a point of contact that resists a desired load -- with as few probing actions as possible. The proposed method repeatedly performs inference, planning, and execution steps. Given a prior probability distribution over object shape and sensor readings from previously executed motions, the posterior distribution is inferred using a novel and efficient Hamiltonian Monte Carlo method. The optimal docking site is chosen to maximize docking probability, using a closed-form probabilistic simulation that accepts rigid and compliant motion models under Coulomb friction. Numerical experiments demonstrate that this method requires fewer exploration actions to dock than heuristics and information-gain strategies.



    AUTHOR    = {Kris Hauser}, 
    TITLE     = {Bayesian Tactile Exploration for Compliant Docking With Uncertain Shapes}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2018}, 
    ADDRESS   = {Pittsburgh, Pennsylvania}, 
    MONTH     = {June}, 
    DOI       = {10.15607/RSS.2018.XIV.051}