This paper describes the development of a terrain-aided localization framework for autonomous land vehicles operating at high speeds in unstructured, expansive and harsh environments. The localization framework developed is sufficiently generic to be used on a variety of other autonomous land vehicles and is demonstrated by its implementation using field data collected from two different trials on two different vehicles. The results demonstrate the robustness of the proposed localization algorithms in producing reliable and accurate position estimates for autonomous vehicles operating in a variety of unstructured domains.
Proceedings of the 19th Symposium on Automation and Robotics in Construction, ISARC 2002
September 23-25, 2002
Symposium on Automation and Robotics in Construction
entropy, extended Kalman filter, iterative closest point, map building, outdoor localization, scale space
Terrain Aided Localization of Autonomous Vehicles, Proceedings of the 19th Symposium on Automation and Robotics in Construction, ISARC 2002, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=824482
(Accessed December 8, 2023)