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Online approximation of an infinite horizon optimal path-following strategyfor a kinematic unicycle is considered. The solution to the optimal controlproblem is approximated using an approximate dynamic programming technique thatuses concurrent-learning-based adaptive update laws to estimate the unknownvalue function. The developed controller overcomes challenges with theapproximation of the infinite horizon value function using an auxiliaryfunction that describes the motion of a virtual target on the desired path. Thedeveloped controller guarantees uniformly ultimately bounded (UUB) convergenceof the vehicle to a desired path while maintaining a desired speed profile andUUB convergence of the approximate policy to the optimal policy. Simulationresults are included to demonstrate the controller's performance.

Online Approximate Optimal Path-Following for a Kinematic Unicycle