Distributed Localization of Modular Robot Ensembles

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.