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Fusion of Multi-Sensor Data Collected by Military Robots

Sanguk Noh and Kyuseon Lee
School of Computer Science and Information Engineering, The Catholic University of Korea, Republic of Korea

Abstract—This paper addresses the fusion processing techniques of multi-sensor data perceived through IR sensors of the military robots for surveillance, in which they are positioned in a limited range with a close distance between each of the robots. To combine multi-sensor data from distributed battlefield robots, we propose a set of fusion rules to formulate the combined prediction from multi-source data expressed in degrees of reliability for the type of a target that has the mathematical properties of probabilities. We have implemented three fusion operators to compare the capabilities of their fusion processing, and have experimented them in simulated, uncertain battlefield environments. The experimental results show that the fusion of multi-sensor data from military robots can be successfully tested in randomly generated military scenarios.

Index Terms—Military surveillance robots, Multi-sensor fusion, Techniques for fusion processing

Cite: Sanguk Noh and Kyuseon Lee, "Fusion of Multi-Sensor Data Collected by Military Robots," Journal of Automation and Control Engineering, Vol.1, No.2, pp. 95-98, June 2013. doi: 10.12720/joace.1.2.95-98
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