Global Manipulation Planning in Robot Joint Space With Task Constraints

Stilman, Mike

Title:

Global Manipulation Planning in Robot Joint Space With Task Constraints

dc.contributor.author	Stilman, Mike
dc.contributor.corporatename	Georgia Institute of Technology. College of Computing
dc.date.accessioned	2010-12-14T19:53:13Z
dc.date.available	2010-12-14T19:53:13Z
dc.date.issued	2010-06
dc.description	© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.	en_US
dc.description	Stilman, M.; "Global Manipulation Planning in Robot Joint Space With Task Constraints," Robotics, IEEE Transactions on , vol.26, no.3, pp.576-584, June 2010 doi: 10.1109/TRO.2010.2044949 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5467152&isnumber=5477213
dc.description.abstract	We explore global randomized joint space path planning for articulated robots that are subject to task space constraints. This paper describes a representation of constrained motion for joint space planners and develops two simple and efficient methods for constrained sampling of joint configurations: Tangent Space Sampling (TS) and First-Order Retraction (FR). FR is formally proven to provide global sampling for linear task space transformations. Constrained joint space planning is important for many real world problems involving redundant manipulators. On the one hand, tasks are designated in work space coordinates: rotating doors about fixed axes, sliding drawers along fixed trajectories or holding objects level during transport. On the other, joint space planning gives alternative paths that use redundant degrees of freedom to avoid obstacles or satisfy additional goals while performing a task. We demonstrate that our methods are faster and more invariant to parameter choices than existing techniques.	en_US
dc.identifier.citation	M. Stilman Global Manipulation Planning in Robot Joint Space With Task Constraints. IEEE Transactions on Robotics, 26(3):576-584, June 2010.	en_US
dc.identifier.issn	1552-3098
dc.identifier.uri	http://hdl.handle.net/1853/36414
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.publisher.original	Institute of Electrical and Electronics Engineers
dc.subject	Robots	en_US
dc.subject	Joint space planning	en_US
dc.subject	Task constraints	en_US
dc.title	Global Manipulation Planning in Robot Joint Space With Task Constraints	en_US
dc.type	Text
dc.type.genre	Article
dspace.entity.type	Publication
local.contributor.corporatename	Humanoid Robotics Laboratory
relation.isOrgUnitOfPublication	05bf85fb-965e-425d-af8b-dbf56e0d9797