Road detection and tracking for autonomous mobile robots

Tsai Hong Hong; Christopher Rasmussen; Tommy Chang; Michael Shneier

doi:10.1117/12.474463

17 July 2002 Road detection and tracking for autonomous mobile robots

Tsai Hong Hong, Christopher Rasmussen, Tommy Chang, Michael Shneier

Proceedings Volume 4715, Unmanned Ground Vehicle Technology IV; (2002) https://doi.org/10.1117/12.474463
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

As part of the Army's Demo III project, a sensor-based system has been developed to identify roads and to enable a mobile robot to drive along them. A ladar sensor, which produces range images, and a color camera are used in conjunction to locate the road surface and its boundaries. Sensing is used to constantly update an internal world model of the road surface. The world model is used to predict the future position of the road and to focus the attention of the sensors on the relevant regions in their respective images. The world model also determines the most suitable algorithm for locating and tracking road features in the images based on the current task and sensing information. The planner uses information from the world model to determine the best path for the vehicle along the road. Several different algorithms have been developed and tested on a diverse set of road sequences. The road types include some paved roads with lanes, but most of the sequences are of unpaved roads, including dirt and gravel roads. The algorithms compute various features of the road images including smoothness in the world model map and in the range domain, and color features and texture in the color domain. Performance in road detection and tracking are described and examples are shown of the system in action.

Citation Download Citation

Tsai Hong Hong, Christopher Rasmussen, Tommy Chang, and Michael Shneier "Road detection and tracking for autonomous mobile robots", Proc. SPIE 4715, Unmanned Ground Vehicle Technology IV, (17 July 2002); https://doi.org/10.1117/12.474463

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available