Self-training cognitive preview control for autonomous vehicle path navigation

Author

Cheok, Ka C. ; Loh, N.K. ; Hu, H.X.

Author_Institution

Center for Robotics & Adv. Autom., Oakland Univ., Rochester, MI, USA

fYear

1988

fDate

7-9 Dec 1988

Firstpage

2286

Abstract

A description is given of a cognitive preview control strategy for autonomous-vehicle steering and cruise guidance by combining optimal preview control theory with rule-based perceptive cruise command generation. The authors also propose a self-training cognition procedure for determining a suitable perceptive schedule for cognitive cruise and steering control. The control yields humanlike driving action in path navigation. It is an intelligent control that decides the cruising speed, plans its control action, and learns the limitation of its steering control. The strategy is being simulated and tested on an autonomous robotic vehicle testbed which is designed for intelligent control experimentation

Keywords

artificial intelligence; learning systems; mobile robots; navigation; position control; predictive control; self-adjusting systems; artificial intelligence; autonomous vehicle; cognitive preview control; cruise guidance; intelligent control; mobile robots; path navigation; rule-based perceptive cruise command; self-training; steering control; Cognition; Cognitive robotics; Control theory; Intelligent control; Intelligent robots; Mobile robots; Navigation; Optimal control; Remotely operated vehicles; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1988., Proceedings of the 27th IEEE Conference on

Conference_Location

Austin, TX

Type

conf

DOI

10.1109/CDC.1988.194744

Filename

194744