The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Robotic manipulation systems suffer from two main problems in unstructured human environments: uncertainty and clutter. We introduce a planning framework addressing these two issues. The framework plans rearrangement of clutter using non-prehensile actions, such as pushing. Pushing actions are also used to manipulate object pose uncertainty. The framework uses an action library that is derived analytically from the mechanics of pushing and is provably conservative. The framework reduces the problem to one of combinatorial search, and demonstrates planning times on the order of seconds. With the extra functionality, our planner succeeds where traditional grasp planners fail, and works under high uncertainty by utilizing the funneling effect of pushing. We demonstrate our results with experiments in simulation and on HERB, a robotic platform developed at the Personal Robotics Lab at Carnegie Mellon University.

Keywords

Manipulation among movable obstacles, Manipulation under uncertainty, Non-prehensile manipulation, Pushing

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): Personal Robotics

Number of pages: 20

Text Reference

Mehmet Dogar and Siddhartha Srinivasa, "A Planning Framework for Non-Prehensile Manipulation under Clutter and Uncertainty," Autonomous Robots, Vol. 33, No. 3, June, 2012, pp. 217-236.

BibTeX Reference

@article{Dogar_2012_7080,
   author = "Mehmet Dogar and Siddhartha Srinivasa",
   title = "A Planning Framework for Non-Prehensile Manipulation under Clutter and Uncertainty",
   journal = "Autonomous Robots",
   pages = "217-236",
   month = "June",
   year = "2012",
   volume = "33",
   number = "3",
}

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