2009 RSS RSS 2009

Rut detection and following for autonomous ground vehicles

Abstract

Expert off road drivers have found through experience that ruts formed on soft terrains as a result of vehicular transit can be used to improve vehicle safety and performance. Rut following improves vehicle performance by reducing the energy wasted on compacting the ground as the vehicle traverses over the terrain. Furthermore, proper rut following can improve vehicle safety on turns and slopes by utilizing the extra lateral force provided by the ruts to reduce lateral slippage and guide the vehicle through its path. This paper presents a set of field experiments to show the relevance of rut following for autonomous ground vehicles and proposes a reactive based approach based on knowledge of the width of the tires and the vehicle body clearance to provide mobile robots with rut detection and following abilities. Experimental results on a Pioneer 3AT robot show that the proposed system was able to detect and follow S-shaped ruts, and ruts that are not directly in front or parallel to the robot. Download: Bibtex: @INPROCEEDINGS{ Ordonez-RSS-09, AUTHOR = {C. Ordonez AND O. Y. Chuy Jr. AND E. G. Collins Jr.}, TITLE = {Rut detection and following for autonomous ground vehicles}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2009}, ADDRESS = {Seattle, USA}, MONTH = {June}, DOI = {10.15607/RSS.2009.V.014} }

🌉 Interdisciplinary Bridge — Artificial Intelligence and Robotics
📈 Trend Setter — Autonomous Vehicles
🧭 Keyword Pioneer — terrain traversal
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Machine Learning, Mathematics & Optimization, Reinforcement Learning, Robotics