Adaptive collaborative estimation of multi-agent mobile robotic systems

Collaborative multi-robot systems are used in a vast array of fields for their innate ability to parallelize domain problems for faster execution. These systems are generally comprised of multiple identical robotic systems in order to simplify manufacturability and programmability, reduce cost, and provide fault tolerance. This work takes advantage of the homogeneity and multiplicity of multi-robot systems to enhance the convergence rate of adaptive dynamic parameter estimation through collaboration. The collaborative adaptive dynamic parameter estimation of multi-robot systems is accomplished by penalizing the pair-wise disagreement of both state and parameter estimates. Consensus and convergence is based on Lyapunov stability arguments. Simulation studies with multiple Pioneer 3-DX systems provides verification of the proposed theoretic collaborative adaptive parameter estimation predictions.