High-speed hazard avoidance for mobile robots in rough terrain

Matthew J. Spenko; Karl D. Iagnemma; Steven Dubowsky

doi:10.1117/12.553242

2 September 2004 High-speed hazard avoidance for mobile robots in rough terrain

Matthew J. Spenko, Karl D. Iagnemma, Steven Dubowsky

Proceedings Volume 5422, Unmanned Ground Vehicle Technology VI; (2004) https://doi.org/10.1117/12.553242
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

Mobile robots have important applications in high speed, rough-terrain scenarios. In these scenarios, unexpected and hazardous situations can occur that require rapid hazard avoidance maneuvers. At high speeds, there is limited time to perform re-planning based on detailed vehicle and terrain models. Furthermore, detailed models often do not accurately predict the robot’s performance due to model parameter and sensor uncertainty. This paper presents a method for high speed hazard avoidance. The method is based on the concept of the trajectory space, which is a compact model-based representation of a robot’s dynamic performance limits in uneven, natural terrain. A Monte Carlo method for analyzing system performance despite model parameter uncertainty is briefly presented, and its integration with the trajectory space is discussed. Simulation results for the hazard avoidance algorithm are presented and demonstrate the effectiveness of the method.

Citation Download Citation

Matthew J. Spenko, Karl D. Iagnemma, and Steven Dubowsky "High-speed hazard avoidance for mobile robots in rough terrain", Proc. SPIE 5422, Unmanned Ground Vehicle Technology VI, (2 September 2004); https://doi.org/10.1117/12.553242

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