Task Constrained Motion Planning in Robot Joint Space

Michael Stilman
tech. report CMU-RI-TR-06-43, Robotics Institute, Carnegie Mellon University, September, 2006


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Abstract
We explore randomized joint space path planning for articulated robots that are subject to task space constraints.This paper presents 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.

Keywords
task constraint, motion planning, configuration space, joint space, path planning

Notes

Text Reference
Michael Stilman, "Task Constrained Motion Planning in Robot Joint Space," tech. report CMU-RI-TR-06-43, Robotics Institute, Carnegie Mellon University, September, 2006

BibTeX Reference
@techreport{Stilman_2006_5583,
   author = "Michael Stilman",
   title = "Task Constrained Motion Planning in Robot Joint Space",
   booktitle = "",
   institution = "Robotics Institute",
   month = "September",
   year = "2006",
   number= "CMU-RI-TR-06-43",
   address= "Pittsburgh, PA",
}