Towards Coordinated Precision Assembly with Robot Teams
Name
DogEtal14.pdf
Description
Accepted version
Size
6.06 MB
Format
Adobe PDF
Checksum (MD5)
50a97703cd51d7fa306da339c76227a5
Author(s)
Dogar, Mehmet
Knepper, Ross A.
Spielberg, Andrew
Choi, Changhyun
Christensen, Henrik I.
Rus, Daniela
Date Issued
November 13, 2015
Publisher
Springer International Publishing
Citation
Dogar, Mehmet, Knepper, Ross A., Spielberg, Andrew, Choi, Changhyun, Christensen, Henrik I. et al. 2015. "Towards Coordinated Precision Assembly with Robot Teams."
Version
Author's final manuscript
Abstract
© Springer International Publishing Switzerland 2016. We present a system in which a flexible team of robots coordinates to assemble large, complex, and diverse structures autonomously. Our system operates across a wide range of spatial scales and tolerances, using a hierarchical perception architecture. For the successful execution of very precise assembly operations under initial uncertainty, our system starts with high-field of view but low accuracy sensors, and gradually uses low field-of-view but high accuracy sensors. Our system also uses a failure detection and recovery system, integrated with this hierarchical perception architecture: upon losing track of a feature, our system retracts to using high-field of view systems to re-localize. Additionally, we contribute manipulation skills and tools necessary to assemble large structures with high precision. First, the team of robots coordinates to transport large assembly parts which are too heavy for a single robot to carry. Second, we develop a new tool which is capable of co-localizing holes and fasteners for robust insertion and fastening. We present real robot experiments where we measure the contribution of the hierarchical perception and failure recovery approach to the robustness of our system. We also present an extensive set of experiments where our robots successfully insert all 80 of the attempted fastener insertion operations.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/978-3-319-23778-7_43
