Approximate Structure Construction Using Large Statistical Swarms
This addresses the challenge of decentralized structure construction for robotic swarms in discrete environments, though it appears incremental as it builds on existing swarm methods.
The paper tackles the problem of enabling large statistical swarms to construct approximate structures in an environment without localization, using harmonic attractor dynamics, with initial results demonstrating the algorithm's feasibility.
In this paper we describe a novel local algorithm for large statistical swarms using "harmonic attractor dynamics", by means of which a swarm can construct harmonics of the environment. This in turn allows the swarm to approximately reconstruct desired structures in the environment. The robots navigate in a discrete environment, completely free of localization, being able to communicate with other robots in its own discrete cell only, and being able to sense or take reliable action within a disk of radius $r$ around itself. We present the mathematics that underlie such dynamics and present initial results demonstrating the proposed algorithm.