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Information-based Intelligent Unmanned Ground Vehicle Navigation

Published

Author(s)

Rajmohan (. Madhavan, Elena R. Messina

Abstract

Abstract?Sensor-centric navigation of Unmanned Ground Vehicles (UGVs) operating in rugged and expansive terrains requires the competency to evaluate the utility of sensor information such that it results in intelligent behavior of the vehicles. In this paper, we propose an entropic information metric for the above purpose where entropy is used to quantify the probabilistic uncertainty in sensor measurements. We present results using data obtained from field trials on an unmanned vehicle to substantiate the utility of the proposed metric. We also show how low and high level tasks can be predicated upon this metric in potential application areas related to autonomous vehicle navigation.
Proceedings Title
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
Conference Dates
October 1, 2003
Conference Location
Las Vegas, NV, USA
Conference Title
IEEE/RSJ International Conference on Intelligent Robots and Systems

Keywords

Behavior Generation, Entropy, Information Evaluation, LADAR, Performance Metrics, Robotics & Intelligent Systems, Sensory Uncertainty, UGV, Unmanned Systems

Citation

Madhavan, R. and Messina, E. (2003), Information-based Intelligent Unmanned Ground Vehicle Navigation, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822571 (Accessed April 24, 2024)
Created September 30, 2003, Updated October 12, 2021