Madhavan, R.
and Schlenoff, C.
(2003),
Moving Object Prediction for Off-road Autonomous Navigation, Proceedings of the SPIE Aerosense Conference, Orlando, FL, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822578
(Accessed January 15, 2025)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Moving Object Prediction for Off-road Autonomous Navigation
Published
Author(s)
,
Abstract
The realization of on- and off-road autonomous navigation of Unmanned Ground Vehicles (UGVs) requires real-time motion planning in the presence of dynamic objects with unknown trajectories. To successfully plan paths and to navigate in an unstructured environment, the UGVs should have the difficult and computationally intensive competency to predict the future locations of moving objects that could interfere with its path. This paper details the development of a combined probabilistic object classification and estimation theoretic framework to predict the future location of moving objects, along with an associated uncertainty measure. The development of a moving object testbed that facilitates the testing of different representations and prediction algorithms in an implementation-independent platform is also outlined.Proceedings Title
Proceedings of the SPIE Aerosense Conference
Conference Dates
April 21-25, 2003
Conference Location
Orlando, FL
Conference Title
SPIE Aerosense Conference
Pub Type
Conferences
Download Paper
Keywords
autonomous navigation, estimation theory., moving object prediction, path planning, uncertainty measure
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created April 25, 2003, Updated February 17, 2017