Global and robust formation-shape stabilization of relative sensing networks

Authors:
Jorge Cortés
Affiliations:
Department of Mechanical and Aerospace Engineering, University of California, 9500 Gilman Drive, San Diego, United States
Venue:
Automatica (Journal of IFAC)
Year:
2009

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Abstract

This paper proposes a simple, distributed algorithm that achieves global stabilization of formations for relative sensing networks in arbitrary dimensions with fixed topology. Assuming the network runs an initialization procedure to equally orient all agent reference frames, convergence to the desired formation shape is guaranteed even in partially asynchronous settings. We characterize the algorithm robustness against several sources of errors: link failures, measurement errors, and frame initialization errors. The technical approach combines algebraic graph theory, multidimensional scaling, and distributed linear iterations.