Title:
Global Manipulation Planning in Robot Joint Space With Task Constraints
Global Manipulation Planning in Robot Joint Space With Task Constraints
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). 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.
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Date Issued
2010-06
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Text
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Article