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Stochastic optimal enhancement of distributed formation control using Kalman smoothers

Published online by Cambridge University Press:  31 January 2014

Ross P. Anderson  and
Dejan Milutinović
Ross P. Anderson
Affiliation:
Department of Applied Mathematics and Statistics, Mail Stop SOEGrad, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA
Dejan Milutinović*
Affiliation:
Computer Engineering Department, Mail Stop SOE2, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA
*
*Corresponding author. E-mail: [email protected]
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Summary

Beginning with a deterministic distributed feedback control for nonholonomic vehicle formations, we develop a stochastic optimal control approach for agents to enhance their non-optimal controls with additive correction terms based on the Hamilton–Jacobi–Bellman equation, making them optimal and robust to uncertainties. In order to avoid discretization of the high-dimensional cost-to-go function, we exploit the stochasticity of the distributed nature of the problem to develop an equivalent Kalman smoothing problem in a continuous state space using a path integral representation. Our approach is illustrated by numerical examples in which agents achieve a formation with their neighbors using only local observations.

Keywords

Multi-robot systemsControl of robotic systemsMotion planningMobile robots
Type
Articles
Information
Robotica , Volume 32 , Issue 2: Distributed Autonomous Robotic Systems (DARS). , March 2014 , pp. 305 - 324
Copyright
Copyright © Cambridge University Press 2014 

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