The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

This paper explores the planning and control of a manipulation task accomplished in conditions of high uncertainty. Statistical techniques, like particle ﬁlters, provide a framework for expressing the uncertainty and partial observability of the real world and taking actions to reduce them. We explore a classic manipulation problem of planar batting, but with a new twist of shape, pose and impact uncertainty. We demonstrate a technique for characterizing and reducing this uncertainty using a particle ﬁlter coupled with a lookahead planner that maximizes information gain. We show that a twostep planner that ﬁrst acts for information gain and then acts to maximize the expectation of achieving a desired goal is effective at managing shape, pose and impact uncertainty

Notes

Text Reference

Jiaxin Fu, Siddhartha Srinivasa, Nancy Pollard, and Bart Nabbe, "Planar batting under shape, pose, and impact uncertainty," Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy, April, 2007.

BibTeX Reference

@inproceedings{Fu_2007_7289,
   author = "Jiaxin Fu and Siddhartha Srinivasa and Nancy Pollard and Bart Nabbe",
   title = "Planar batting under shape, pose, and impact uncertainty",
   booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy",
   month = "April",
   year = "2007",
   number= "CMU-RI-TR-",
}

The Robotics Institute

Menu