Robotics: Science and Systems IX

Active Bayesian Perception for Simultaneous Object Localization and Identification

Nathan Lepora, Uriel Martinez-Hernandez, Tony Prescott


In this paper, we propose that active Bayesian perception has a general role for Simultaneous Object Localization and IDentification (SOLID), or deciding where and what. We test this claim using a biomimetic fingertip to perceive object identity via surface shape at uncertain contact locations. Our method for active Bayesian perception combines decision making by threshold crossing of the posterior belief with a sensorimotor loop that actively controls sensor location based on those beliefs. Our findings include: (i) active perception with a fixation control strategy gives an order-of-magnitude improvement in acuity over passive perception without sensorimotor feedback; (ii) perceptual acuity improves as the active control requires less belief to~make a relocation decision; and (iii) relocation noise further improves acuity. The best method has aspects that resemble animal perception, supporting wide applicability of these findings.



    AUTHOR    = {Nathan Lepora AND Uriel Martinez-Hernandez AND Tony Prescott}, 
    TITLE     = {Active Bayesian Perception for Simultaneous Object Localization and Identification}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2013}, 
    ADDRESS   = {Berlin, Germany}, 
    MONTH     = {June},
    DOI       = {10.15607/RSS.2013.IX.019}