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Carnegie Mellon Robotics Institute

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Abstract

In this paper, we address the problem of Navigation Among Movable Obstacles (NAMO):a practical extension to navigation for humanoids and other dexterous mobile robots. The robot is permitted to reconfigure the environment by moving obstacles and clearing free space for a path. Simpler problems have been shown to be P-SPACE hard. For real-world scenarios with large numbers of movable obstacles, complete motion planning techniques are largely intractable. This paper presents a resolution complete planner for a subclass of NAMO problems. Our planner takes advantage of the navigational structure through state-space decomposition and heuristic search. The planning complexity is reduced to the difficulty of the specific navigation task, rather than the dimensionality of the multi-object domain. We demonstrate real-time results for spaces that contain large numbers of movable obstacles. We also present a practical framework for single-agent search that can be used in algorithmic reasoning about this domain.

Notes

Associated Center(s) / Consortia: Center for the Foundations of Robotics

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

Associated Project(s): Navigation Among Movable Obstacles

Number of pages: 20

Text Reference

Michael Stilman and James Kuffner, "Navigation Among Movable Obstacles: Real-time Reasoning in Complex Environments," Proceedings of the 2004 IEEE International Conference on Humanoid Robotics (Humanoids'04), December, 2004, pp. 322 - 341.

BibTeX Reference

@inproceedings{Stilman_2004_4854,
   author = "Michael Stilman and James Kuffner",
   title = "Navigation Among Movable Obstacles: Real-time Reasoning in Complex Environments",
   booktitle = "Proceedings of the 2004 IEEE International Conference on Humanoid Robotics (Humanoids'04)",
   pages = "322 - 341",
   month = "December",
   year = "2004",
   volume = "1",
}

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