Task Constrained Motion Planning in Robot Joint Space

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/36455

Title: Task Constrained Motion Planning in Robot Joint Space
Author: Stilman, Mike
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.
Description: © 2007 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.
Type: Proceedings
URI: http://hdl.handle.net/1853/36455
Citation: M. Stilman, Task Constrained Motion Planning in Robot Joint Space. IEEE Int. Conf. on Intelligent Robots and Systems (IROS’07), October 2007.
Date: 2007-10
Contributor: Carnegie-Mellon University. Robotics Institute
Publisher: Georgia Institute of Technology
Institute of Electrical and Electronics Engineers
Subject: Articulated robots
Joint space planning
Motion planning

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