The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

We present an efficient approach to generating paths for a robotic manipulator that are collision-free and guaranteed to meet task specifications despite pose uncertainty. We first describe how to use Task Space Regions (TSRs) to specify grasping and object placement tasks for a manipulator. We then show how to modify a set of TSRs for a certain task to take into account pose uncertainty. A key advantage of this approach is that if the pose uncertainty is too great to accomplish a certain task, we can quickly reject that task without invoking a planner. If the task is not rejected we run the IKBiRRT planner, which trades-off exploring the robot's C-space with sampling from TSRs to compute a path. Finally, we show several examples of a 7-DOF WAM arm planning paths in a cluttered kitchen environment where the poses of all objects are uncertain.

Keywords

manipulation planning, planning with uncertainty, sampling-based planning

Notes

Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics

Associated Lab(s) / Group(s): Planning and Autonomy Lab and Personal Robotics

Associated Project(s): Planning for Manipulation

Text Reference

Dmitry Berenson, Siddhartha Srinivasa, and James Kuffner, "Addressing Pose Uncertainty in Manipulation Planning Using Task Space Regions," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09), October, 2009.

BibTeX Reference

@inproceedings{Berenson_2009_6415,
   author = "Dmitry Berenson and Siddhartha Srinivasa and James Kuffner",
   title = "Addressing Pose Uncertainty in Manipulation Planning Using Task Space Regions",
   booktitle = "IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09)",
   month = "October",
   year = "2009",
}

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