Active Extrinsic Contact Sensing: Application to General Peg-in-Hole Insertion
Name
2022-ICRA-Active Extrinsic Contact Sensing-final.pdf
Description
Accepted version
Size
1.51 MB
Format
Adobe PDF
Checksum (MD5)
fe2358075fded4f181757a07851f401f
Author(s)
Kim, Sangwoon
Rodriguez, Alberto
Date Issued
May 23, 2022
Publisher
IEEE|2022 International Conference on Robotics and Automation (ICRA)
Citation
Kim, Sangwoon and Rodriguez, Alberto. 2022. "Active Extrinsic Contact Sensing: Application to General Peg-in-Hole Insertion." 00.
Version
Author's final manuscript
Abstract
We propose a method that actively estimates contact location between a grasped rigid object and its environment
and uses this as input to a peg-in-hole insertion policy. An
estimation model and an active tactile feedback controller work
collaboratively to estimate the external contacts accurately. The
controller helps the estimation model get a better estimate by
regulating a consistent contact mode. The better estimation
makes it easier for the controller to regulate the contact. We
then train an object-agnostic insertion policy that learns to
use the series of contact estimates to guide the insertion of an
unseen peg into a hole. In contrast with previous works that
learn a policy directly from tactile signals, since this policy
is in contact configuration space, it can be learned directly
in simulation. Lastly, we demonstrate and evaluate the active
extrinsic contact line estimation and the trained insertion policy
together in a real experiment. We show that the proposed
method inserts various-shaped test objects with higher success
rates and fewer insertion attempts than previous work with
end-to-end approaches. See supplementary video and results at
https://sites.google.com/view/active-extrinsic-contact.
Description
2022 IEEE International Conference on Robotics and Automation (ICRA) May 23-27, 2022. Philadelphia, PA, USA
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-ShareAlike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/icra46639.2022.9812017
