Distributed Localization of Modular Robot Ensembles

Authors:
Stanislav Funiak;Padmanabhan Pillai;Michael P. Ashley-Rollman;Jason D. Campbell;Seth Copen Goldstein
Affiliations:
Carnegie Mellon University, Pittsburgh, PA 15213, USA/;Intel Research Pittsburgh, Pittsburgh, PA 15213, USA/;Carnegie Mellon University, Pittsburgh, PA 15213, USA/;Intel Research Pittsburgh, Pittsburgh, PA 15213, USA,;Carnegie Mellon University, Pittsburgh, PA 15213, USA,
Venue:
International Journal of Robotics Research
Year:
2009

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Abstract

Internal localization, the problem of estimating relative pose for each module 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 sub-regions with small mutual localization error, then progressively merges those sub-regions to localize the entire ensemble. Our method works well in both two and three dimensions, and requires neither exact measurements nor rigid inter-module connectors. Most of the computations in our method can be distributed effectively. The result is a robust algorithm that scales to large ensembles. We evaluate our algorithm in two- and three-dimensional simulations of scenarios with up to 10,000 modules.