A Framework for Predicting the Mission-Specific Performance of Autonomous Unmanned Systems
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014) 2014
Phillip Durst, Wendell Gray, Agris Ņikitenko, João Caetano, Michael Trentini, Roger King

While many methodologies have been proposed for calculating a quantitative level of autonomy for intelligent Unmanned Systems (UMS), no one definitive measure of autonomy or autonomous performance has been validated and adopted by the UMS community. Particularly for military applications, a simple performance metric that is based on the UMSs mission profile and is comparable between UMS systems is critical. This metric would not only help define the features a UMS needs to successfully perform its mission, both in terms of hardware and software, but also enable the use of UMS for a broader range of applications at an increased level of autonomy. This paper presents the development of a new methodology for calculating a single-number performance metric for autonomous UMS, and this metric is called the Mission Performance Potential (MPP). Rather than a retroactive measure of UMS performance and autonomy level for one iteration of a given scenario, the MPP separates autonomy level and mission performance to provide a predictive measure of a UMS's expected performance for a mission set and level of autonomy. As an example application, the MPP is calculated for an Unmanned Aerial Vehicle (UAV) performing a target tracking mission, and this MPP value is compared to the results of field-testing with this system.


Atslēgas vārdi
Intelligent unmanned systems, unmanned aerial vehicles, mission performance, target tracking
DOI
10.1109/IROS.2014.6942823
Hipersaite
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6942823

Durst, P., Gray, W., Ņikitenko, A., Caetano, J., Trentini, M., King, R. A Framework for Predicting the Mission-Specific Performance of Autonomous Unmanned Systems. No: Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), Amerikas savienotās valstis, Chicago, 14.-18. septembris, 2014. Piscataway: IEEE, 2014, 1962.-1969.lpp. ISBN 978-147996934-0. ISSN 2153-0858. Pieejams: doi:10.1109/IROS.2014.6942823

Publikācijas valoda
English (en)
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