2026-09-19T08:33:41Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1157392021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Russ Tedrake.
Manuelli, Lucas, Ph. D. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2018-05-23T16:32:38Z
2018-05-23T16:32:38Z
2018
2018
http://hdl.handle.net/1721.1/115739
1036986776
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 61-65).
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 the 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. The 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 in multiple scenarios. We show how it can track multiple external contacts on a simulated Atlas robot, and also perform extensive simulation and hardware experiments on a Kuka iiwa robot arm.
by Lucas Manuelli.
S.M.
65 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Localizing external contact using proprioceptive sensors : the contact particle filter
Thesis
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<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 the 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. The 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 in multiple scenarios. We show how it can track multiple external contacts on a simulated Atlas robot, and also perform extensive simulation and hardware experiments on a Kuka iiwa robot arm.</Abstract>
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