Dynamic coordinated control laws in multiple agent models

We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in \cite{JK04}, gives rise to spontaneous collective organization of agents into a unified coherent swarm, via a long-range attractive and short-range repulsive potential. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously.Comment: 20 pages, 6 figure

Reaction-diffusion patterns in smart sensor networks

technical reportWe introduced the use of Turing?s reaction-diffusion pattern formation to support high-level tasks in smart sensor networks (S-Nets). This has led us to explore various biologically motivated mechanisms. In this paper we address some issues that arise in trying to get reliable, efficient patterns in irregular grids with error in inter-node distances

Pattern formation in wireless sensor networks

technical reportBiological systems exhibit an amazing array of distributed sensor/actuator systems, and the exploitation of principles and practices found in nature will lead to more effective artificial systems. The retina is an example of a highly tuned sensing organ, and the human skin is comprised of a set of heterogeneous sensor and actuator elements. Moreover, the specific organization and architecture of these systems depends on contextual influences during the developmental stages of the organism. Comparable theoretical and technological methodologies need to be found for wireless sensor networks. We propose the study of reaction-diffusion systems from mathematical biology as a starting point for this endeavor. Algorithms and experiments are described here for a useful set of pattern formation methods in wireless sensor networks