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

Internal localization, the problem of estimating relative pose for each module (part) of a modular robot is a prerequisite for many shape control, locomotion, and actuation algorithms. In this paper, we propose a robust hierarchical approach that uses normalized cut to identify dense subregions with small mutual localization error, then progressively merges those subregions to localize the entire ensemble. Our method works well in both 2D and 3D, and requires neither exact measurements nor rigid inter-module connectors. Most of the computations in our method can be effectively distributed. The result is a robust algorithm that scales to large, non-homogeneous ensembles. We evaluate our algorithm in accurate 2D and 3D simulations of scenarios with up to 10,000 modules.

Keywords

Distributed Systems, Localization

Notes

Text Reference

Stanislav Funiak, Padmanabhan Pillai, Michael Ashley-Rollman, Jason Campbell, and Seth Copen Goldstein, "Distributed Localization of Modular Robot Ensembles," Proceedings of Robotics: Science and Systems, 2008.

BibTeX Reference

@inproceedings{Funiak_2008_6177,
   author = "Stanislav Funiak and Padmanabhan Pillai and Michael Ashley-Rollman and Jason Campbell and Seth Copen Goldstein",
   title = "Distributed Localization of Modular Robot Ensembles",
   booktitle = "Proceedings of Robotics: Science and Systems",
   year = "2008",
}

The Robotics Institute

Menu