VISION-BASED UNSUPERVISED LEARNING OF UNEXPLORED ENVIRONMENT FOR AUTONOMOUS LAND VEHICLE NAVIGATION
Guanyu Chen, Wen‐Hsiang Tsai · 1998
In this paper, the authors present a vision-based approach, designed for autonomous land vehicle navigation, which is used for unsupervised learning of the environment. The learning system is comprised of three subsystems: feature location, model management and environment exploration. These three strategies are described. Simulation and experimental results indicate the feasibility of using this proposed approach for a learning system for real environments.