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.

Cooperative multi-robot systems have been used in a vast array of fields and are of particular interest in perilous environments. One of the main issues in multi-robot systems is the lack of a common set of programming and control abstractions and middleware. Controlling and programming cooperative multi-robot systems is a highly complicated task that requires a flexible and agile control architecture and programming environment that are able to handle the distributed nature of multi-robot systems. A generalized, highly flexible and reconflgurable cooperative robot control platform called Mobile-R has been developed. Mobile-R consists of a mobile agent-based robot control system and a mission-based rapid deployment system. A real-world validation experiment involving cooperative multi-robot perimeter patrolling is presented.