Information-based Intelligent Unmanned Ground Vehicle Navigation

Published

October 1, 2003

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

Pub Type

Conferences

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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 October 17, 2025)