Efficient Planning for Near-Optimal Compliant Manipulation Leveraging Environmental Contact
Author(s)
Guan, Charlie; Vega-Brown, William R; Roy, Nicholas
DownloadAccepted version (1.108Mb)
Terms of use
Metadata
Show full item recordAbstract
Path planning classically focuses on avoiding environmental contact. However, some assembly tasks permit contact through compliance, and such contact may allow for more efficient and reliable solutions under action uncertainty. But, optimal manipulation plans that leverage environmental contact are difficult to compute. Environmental contact produces complex kinematics that create difficulties for planning. This complexity is usually addressed by discretization over state and action space, but discretization quickly becomes computationally intractable. To overcome the challenge, we use the insight that only actions on configurations near the contact manifold are likely to involve complex kinematics, while segments of the plan through free space do not. Leveraging this structure can greatly reduce the number of states considered and scales much better with problem complexity. We develop an algorithm based on this idea and show that it performs comparably to full MDP solutions at a fraction of the computational cost.
Date issued
2018-09Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Guan, Charlie et al. "Efficient Planning for Near-Optimal Compliant Manipulation Leveraging Environmental Contact." May 2018, IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, Institute of Electrical and Electronics Engineers (IEEE), September 2018 © 2018 IEEE
Version: Author's final manuscript
ISBN
9781538630815