Robotics: Science and Systems IX
Active Bayesian Perception for Simultaneous Object Localization and Identification
Nathan Lepora, Uriel Martinez-Hernandez, Tony PrescottAbstract:
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.
Bibtex:
@INPROCEEDINGS{Lepora-RSS-13, 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} }