Title :
Online approximate optimal path-following for a mobile robot
Author :
Walters, Patrick ; Kamalapurkar, Rushikesh ; Andrews, Lindsey ; Dixon, Warren E.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
Online approximation of an infinite horizon optimal path-following strategy for a unicycle-type mobile robot is considered. An approximate solution to the optimal control problem is obtained by using an adaptive dynamic programming technique that uses adaptive update laws to estimate the unknown value function. The developed controller overcomes challenges with the approximation of the infinite horizon value function by using an auxiliary function that describes the motion of a virtual target on the desired path. The developed controller guarantees uniformly ultimately bounded (UUB) convergence of the vehicle to a desired path while maintaining a desired speed profile and UUB convergence of the approximate policy to the optimal policy without requiring persistence of excitation.
Keywords :
adaptive control; approximation theory; convergence of numerical methods; dynamic programming; infinite horizon; mobile robots; optimal control; path planning; UUB convergence; adaptive dynamic programming technique; adaptive update laws; approximate policy; auxiliary function; desired path; infinite horizon optimal path-following strategy; infinite horizon value function; online approximate optimal path-following; optimal control problem; optimal policy; speed profile; unicycle-type mobile robot; uniformly ultimately bounded convergence; unknown value function estimation; virtual target; Function approximation; Mobile robots; Stability analysis; Vectors; Vehicle dynamics; Vehicles;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040097