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Paper WeA01.3

Nestinger, Stephen (Worcester Polytechnic Institute), Demetriou, Michael (Worcester Polytechnic Institute)

Adaptive Collaborative Estimation of Multi-Agent Mobile Robotic Systems

Scheduled for presentation during the Regular Session "Learning and Adaptation Control of Robotic Systems II" (WeA01), Wednesday, May 16, 2012, 09:00−09:15, Meeting Room 1 (Mini-sota)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on October 24, 2017

Keywords Learning and Adaptive Systems, Distributed Robot Systems, Calibration and Identification

Abstract

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.

 

 

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