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Information-Based Intelligent Unmanned Ground Vehicle Navigation

Published

Author(s)

Rajmohan Madhavan, Elena R. Messina

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
Intelligent Robots and Systems, International Conference ||2003 IEEE/RSJ International Conference on Intelligent Robots and Systems | IEEE / Robotics Society of Japan
Volume
2003
Issue
4
Conference Dates
October 1, 2003
Conference Title
IEEE International Conference on Intelligent Robots and Systems

Keywords

Behavior Generation, Entropy, Information Evaluation, LADAR, Sensor Uncertainty, UGVs

Citation

Madhavan, R. and Messina, E. (2003), Information-Based Intelligent Unmanned Ground Vehicle Navigation, Intelligent Robots and Systems, International Conference ||2003 IEEE/RSJ International Conference on Intelligent Robots and Systems | IEEE / Robotics Society of Japan (Accessed April 12, 2024)
Created October 1, 2003, Updated February 17, 2017