Internal Localization of Modular Robot Ensembles

Abstract

The determination of the relative position and pose of every robot in a modular robotic ensemble is a necessary preliminary step for most modular robotic tasks. Localization is particularly important when the modules make local noisy observations and are not significantly constrained by interrobot latches. In this paper, we propose a robust hierarchical approach to the internal localization problem that uses normalized cut to identify subproblems with small localization error. A key component of our algorithm is a simple method to reduce the cost of normalized cut computations. The result is a robust algorithm that scales to large, non-homogeneous ensembles. We evaluate our algorithm in simulation on ensembles of up to 10,000 modules.