Task Allocation via Self-Organizing Swarm Coalitions in Distributed Mobile Sensor Network

Kian Hsiang Low, Wee Kheng Leow, and Marcelo H. Ang, Jr.

This paper presents a task allocation scheme via self organizing swarm coalitions for distributed mobile sensor network coverage. Our approach uses the concepts of ant behavior to self-regulate the regional distributions of sensors in proportion to that of the moving targets to be tracked in a non-stationary environment. As a result, the adverse effects of task interference between robots are minimized and sensor network coverage is improved. Quantitative comparisons with other tracking strategies such as static sensor placement, potential fields, and auction-based negotiation show that our approach can provide better coverage and greater flexibility to respond to environmental changes.

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