Autonomous Vehicle Path Tracking Based on Natural Gradient Methods-Reference-Cited by-同舟云学术

Autonomous Vehicle Path Tracking Based on Natural Gradient Methods

Published:2012-11-20 Issue:7 Volume:16 Page:888-893
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Kwon Ki-Young, ,Jung Keun-Woo,Yang Dong-Su,Park Jooyoung,

Abstract

Recently, reinforcement learning and evolution strategy have become major tools in the field of machine learning, and have shown excellent performance in various engineering problems. In particular, the Natural Actor-Critic (NAC) approach and the Natural Evolution Strategies (NES) have led to considerable interests in the area of natural-gradient-based machine learning methods with many successful applications. In this paper, we apply the NAC and the NES to pathtracking control problems for autonomous vehicles. Simulation results show that these methods can yield better performance compared to the conventional PID controllers.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference11 articles.

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