Localizing external contact using proprioceptive sensors: The Contact Particle Filter
Name
Manuelli16.pdf
Description
Accepted version
Size
3.25 MB
Format
Adobe PDF
Checksum (MD5)
b01408408faa95e5c69e20b493a1c890
Author(s)
Manuelli, Lucas
Tedrake, Russell Louis
Date Issued
December 2016
Journal
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Manuelli, 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 IEEE
Version
Author's final manuscript
Abstract
In 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; Observers
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/iros.2016.7759743
