Title:
The Motion Grammar: Linguistic Perception, Planning, and Control
The Motion Grammar: Linguistic Perception, Planning, and Control
| dc.contributor.author | Dantam, Neil | |
| dc.contributor.author | Stilman, Mike | |
| dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | |
| dc.date.accessioned | 2010-12-16T20:48:08Z | |
| dc.date.available | 2010-12-16T20:48:08Z | |
| dc.date.issued | 2010 | |
| dc.description.abstract | We present the Motion Grammar: a novel unified representation for task decomposition, perception, planning, and hybrid control that provides a computationally tractable way to control robots in uncertain environments with guarantees on completeness and correctness. The grammar represents a policy for the task which is parsed in real-time based on perceptual input. Branches of the syntax tree form the levels of a hierarchical decomposition, and the individual robot sensor readings are given by tokens. We implement this approach in the interactive game of Yamakuzushi on a physical robot resulting in a system that repeatably competes with a human opponent in sustained game-play for matches up to six minutes. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1853/36485 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.relation.ispartofseries | GT-GOLEM-2010-001 | en_US |
| dc.subject | Robotics | en_US |
| dc.subject | Manipulation | en_US |
| dc.subject | Formal methods | en_US |
| dc.subject | Grammars | en_US |
| dc.subject | Control | en_US |
| dc.title | The Motion Grammar: Linguistic Perception, Planning, and Control | en_US |
| dc.type | Text | |
| dc.type.genre | Technical Report | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | Humanoid Robotics Laboratory | |
| local.contributor.corporatename | College of Computing | |
| local.relation.ispartofseries | Humanoid Robotics Laboratory Technical Report Series | |
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| relation.isOrgUnitOfPublication | c8892b3c-8db6-4b7b-a33a-1b67f7db2021 | |
| relation.isSeriesOfPublication | e2b4b849-c3fb-4761-b071-c47f921fc942 |