How to Derive the Autonomous Driving Function Level of Unmanned Ground Vehicles - Focusing on Defense Robots - 


Vol. 42,  No. 1, pp. 205-213, Jan.  2017


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  Abstract

This paper is a study on the method to derive the functional level required for autonomous unmanned ground vehicle, one of the defense robots. Conventional weapon systems are not significantly affected by the operating environment, while defense robots exhibit different performance depending on the operating environment, even if they are on the same platform. If the performance of defense robot is different depending on operational environment, results of mission performance will be vary significantly. Therefore, it is necessary to clarify the level of function required by the military in order to research and develop most optimal defense robots. In this thesis, we propose a method to derive the required function level of unmanned ground vehicles, focusing on autonomous driving, one of the most vital functions of defense robots. Our results showed that the autonomous driving function depending intervention levels and evaluated functional sensitivity for autonomous driving of the unmanned vehicle using climate and topography as variables.

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  Cite this article

[IEEE Style]

Y. Kim, Y. Choi, J. Kim, "How to Derive the Autonomous Driving Function Level of Unmanned Ground Vehicles - Focusing on Defense Robots -," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 1, pp. 205-213, 2017. DOI: .

[ACM Style]

Yull-Hui Kim, Yong-Hoon Choi, and Jin-Oh Kim. 2017. How to Derive the Autonomous Driving Function Level of Unmanned Ground Vehicles - Focusing on Defense Robots -. The Journal of Korean Institute of Communications and Information Sciences, 42, 1, (2017), 205-213. DOI: .

[KICS Style]

Yull-Hui Kim, Yong-Hoon Choi, Jin-Oh Kim, "How to Derive the Autonomous Driving Function Level of Unmanned Ground Vehicles - Focusing on Defense Robots -," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 1, pp. 205-213, 1. 2017.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880