Title:
Task-Aware Variations in Robot Motion
Task-Aware Variations in Robot Motion
| dc.contributor.author | Gielniak, Michael J. | en_US |
| dc.contributor.author | Liu, C. Karen | en_US |
| dc.contributor.author | Thomaz, Andrea L. | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Interactive Computing | en_US |
| dc.date.accessioned | 2012-01-24T21:25:10Z | |
| dc.date.available | 2012-01-24T21:25:10Z | |
| dc.date.issued | 2011-05 | |
| dc.description | © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Digital Object Identifier : 10.1109/ICRA.2011.5980348 | en_US |
| dc.description | Presented at the 2011 IEEE International Conference on Robotics and Automation, Shanghai International Conference Center, May 9-13, 2011, Shanghai, China. | |
| dc.description.abstract | Social robots can benefit from motion variance because non-repetitive gestures will be more natural and intuitive for human partners. We introduce a new approach for synthesizing variance, both with and without constraints, using a stochastic process. Based on optimal control theory and operational space control, our method can generate an infinite number of variations in real-time that resemble the kinematic and dynamic characteristics from the single input motion sequence. We also introduce a stochastic method to generate smooth but nondeterministic transitions between arbitrary motion variants. Furthermore, we quantitatively evaluate taskaware variance against random white torque noise, operational space control, style-based inverse kinematics, and retargeted human motion to prove that task-aware variance generates human-like motion. Finally, we demonstrate the ability of task-aware variance to maintain velocity and time-dependent features that exist in the input motion. | en_US |
| dc.identifier.citation | M.J. Gielniak, C.K. Liu and A.L. Thomaz, "Task-aware Variations in Robot Motion." In Proceedings of the International Conference on Robotics and Automation (ICRA), 2011. | en_US |
| dc.identifier.isbn | 978-1-61284-386-5 | |
| dc.identifier.issn | 1050-4729 | |
| dc.identifier.uri | http://hdl.handle.net/1853/42278 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical & Electronics Engineers | en_US |
| dc.subject | Social robots | en_US |
| dc.subject | Non-repetitive gestures | |Human like motion | en_US |
| dc.subject | Motion variance | en_US |
| dc.subject | Task aware variance | en_US |
| dc.title | Task-Aware Variations in Robot Motion | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dc.type.genre | Post-print | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | Socially Intelligent Machines Lab | |
| local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
| relation.isOrgUnitOfPublication | c8892b3c-8db6-4b7b-a33a-1b67f7db2021 | |
| relation.isOrgUnitOfPublication | 57e47d4b-8e04-4c68-a99e-2cb4580b4844 | |
| relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf |
Files
Original bundle
1 - 1 of 1
- Name:
- Task-Aware Variations in Robot Motion.pdf
- Size:
- 1.05 MB
- Format:
- Adobe Portable Document Format
- Description: