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 article compares several parameterizations and motion models for improving the estimation of the nonlinear uncertainty distribution produced by robot motion. In previous work, we have shown that the use of a modiﬁed polar parameterization provides a way to represent nonlinear measurements distributions in the Cartesian space as linear distributions in polar space. Following the same reasoning, we present a motion model extension that utilizes the same polar parameterization to achieve improved modeling of mobile robot motion in between measurements, gaining robustness with no additional overhead. We present both simulated and experimental results to validate the effectiveness of our approach.

Notes

Associated Center(s) / Consortia: Field Robotics Center

Number of pages: 6

Note: (to appear)

Text Reference

Joseph Djugash, Sanjiv Singh, and Benjamin P. Grocholsky, "Modeling Mobile Robot Motion with Polar Representations," Proceedings of IROS 2009, October, 2009.

BibTeX Reference

@inproceedings{Djugash_2009_6431,
   author = "Joseph Djugash and Sanjiv Singh and Benjamin P Grocholsky",
   title = "Modeling Mobile Robot Motion with Polar Representations",
   booktitle = "Proceedings of IROS 2009",
   month = "October",
   year = "2009",
   Notes = "(to appear)"
}

The Robotics Institute

Menu