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dc.contributor.authorManuelli, Lucas
dc.contributor.authorTedrake, Russell Louis
dc.date.accessioned2021-04-13T20:04:51Z
dc.date.available2021-04-13T20:04:51Z
dc.date.issued2016-12
dc.date.submitted2016-10
dc.identifier.isbn9781509037629
dc.identifier.issn2153-0866
dc.identifier.urihttps://hdl.handle.net/1721.1/130471
dc.description.abstractIn order for robots to interact safely and intelligently with their environment they must be able to reliably estimate and localize external contacts. This paper introduces CPF, the Contact Particle Filter, which is a general algorithm for detecting and localizing external contacts on rigid body robots without the need for external sensing. CPF finds external contact points that best explain the observed external joint torque, and returns sensible estimates even when the external torque measurement is corrupted with noise. We demonstrate the capability of the CPF to track multiple external contacts on a simulated Atlas robot, and compare our work to existing approaches. Keywords: Robot sensing systems; Collision avoidance; Legged locomotion; Torque; Observersen_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/iros.2016.7759743en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleLocalizing external contact using proprioceptive sensors: The Contact Particle Filteren_US
dc.typeArticleen_US
dc.identifier.citationManuelli, Lucas and Tedrake, Russ. "Localizing external contact using proprioceptive sensors: The Contact Particle Filter." 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2016, Daejeon, South Korea, Institute of Electrical and Electronics Engineers (IEEE), 2016. © 2016 IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journal2016 IEEE/RSJ International Conference on Intelligent Robots and Systemsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-11T12:52:25Z
dspace.date.submission2019-07-11T12:52:26Z
mit.metadata.statusComplete


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