A SOLID case for active bayesian perception in robot touch

Nathan F. Lepora, Uriel Martinez-Hernandez, Tony J. Prescott

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

5 Citations (Scopus)

Abstract

In a series of papers, we have formalized a Bayesian perception approach for robotics based on recent progress in understanding animal perception. The main principle is to accumulate evidence for multiple perceptual alternatives until reaching a preset belief threshold, formally related to sequential analysis methods for optimal decision making. Here, we extend this approach to active perception, by moving the sensor with a control strategy that depends on the posterior beliefs during decision making. This method can be used to solve problems involving Simultaneous Object Localization and IDentification (SOLID), or 'where and what'. Considering an example in robot touch, we find that active perception gives an efficient, accurate solution to the SOLID problem for uncertain object locations; in contrast, passive Bayesian perception, which lacked sensorimotor feedback, then performed poorly. Thus, active perception can enable robust sensing in unstructured environments.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages154-166
Number of pages13
Volume8064 LNAI
DOIs
Publication statusPublished - 2013
Event2nd International Conference on Biomimetic and Biohybrid Systems: Living Machines, LM 2013 - London, United Kingdom
Duration: 29 Jul 20132 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8064 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference2nd International Conference on Biomimetic and Biohybrid Systems: Living Machines, LM 2013
CountryUnited Kingdom
CityLondon
Period29/07/132/08/13

Keywords

  • Active perception
  • localization
  • robotics
  • tactile sensing

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