Title:
Task Constrained Motion Planning in Robot Joint Space
Task Constrained Motion Planning in Robot Joint Space
Author(s)
Stilman, Mike
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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). 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. In simulation,
we demonstrate that our methods are faster and significantly
more invariant to problem/algorithm parameters than existing
techniques.
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Date Issued
2007-10
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Text
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Proceedings