Localizing external contact using proprioceptive sensors : the contact particle filter
Name
1036986776-MIT.pdf
Description
Full printable version
Size
6.06 MB
Format
Adobe PDF
Checksum (MD5)
ce461c85e36c7dc9bb1040c3c65f40b4
Author(s)
Manuelli, Lucas, Ph. D. Massachusetts Institute of Technology
Advisor(s)
Russ Tedrake.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
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.
Description
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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