Visual Navigation for Mobile Robots: A Survey
Journal of Intelligent and Robotic Systems
A multi-range vision strategy for autonomous offroad navigation
RA '07 Proceedings of the 13th IASTED International Conference on Robotics and Applications
Learning Visual Object Categories for Robot Affordance Prediction
International Journal of Robotics Research
Crossing road monitoring system based on adaptive decision for illegal situation
Applied Soft Computing
Short-range radar perception in outdoor environments
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Self-learning classification of radar features for scene understanding
Robotics and Autonomous Systems
Carotid artery image segmentation using modified spatial fuzzy c-means and ensemble clustering
Computer Methods and Programs in Biomedicine
Neuro fuzzy and punctual kriging based filter for image restoration
Applied Soft Computing
| Hi-index | 0.00 |
The use of artificial neural networks in the domain of autonomous driving has produced promising results. ALVINN has shown that a neural system can drive a vehicle reliably and safely on many different types of roads, ranging from paved paths to interstate highways. The next step in the evolution of autonomous driving systems is to intelligently handle road junctions. In this paper the authors present an addition to the basic ALVINN driving system which makes autonomous detection of roads and traversal of simple intersections possible. The addition is based on geometrically modelling the world, accurately imaging interesting parts of the scene using this model, and monitoring ALVINN's response to the created image.