Directed Self-Organization in Multi-Agent Swarms via Pseudo-Localization Algorithms

Vishaal Krishnan and Sonia Martínez
Proceedings of the 22nd International Symposium on Mathematical Theory of Networks and Systems (MTNS), Minneapolis, MN, USA, July 2016

Abstract:

In this work, we address the problem of self-organization in multi-agent swarms in 1D and 2D spatial domains. We assume that the swarm consists of a very large number of agents and make a continuum approximation, specifying the configuration of the swarm through a spatial density distribution. Each individual agent is capable of measuring the current local density of agents and can communicate with its neighbors. The key feature of this work is that the agents neither have access to position information nor do they have the capability to measure the distances to their neighbors. The agents implement a distributed algorithm, which we call pseudo-localization, to localize themselves in a new coordinate frame, and a distributed control law to converge to the desired spatial density distribution. We start by studying self-organization in one-dimension, which is then followed by the two-dimensional case.

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Bib-tex entry:

@InProceedings{VK-SM:15-mtns},
author = {V. Krishnan and S. Mart{\'\i}nez},
booktitle = {22nd International Symposium on Mathematical Theory of Networks and Systems (MTNS)},
title = {Directed Self-Organization in Multi-Agent Swarms via Pseudo-Localization Algorithms},
month = {July},
year = {2016},
address ={Minneapolis, MN, USA},
pages = {706--713}
}