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Journal Article Strategic optimal control of multi-camera trajectories for UAV capture using entropy and coverage approaches
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Authors
Khishigjargal Gonchigsumlaa, Young-Il Kim, Kun Min Yeo, Seong Hee Park, Yong-Tae Lee
Issue Date
2025-05
Citation
Bulletin of the Polish Academy of Sciences: Technical Sciences, v.73, no.3, pp.1-12
ISSN
0239-7528
Publisher
Polish Academy of Sciences
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.24425/bpasts.2025.153828
Abstract
The widespread use of unmanned aerial vehicles (UAVs) has heightened the demand for effective UAV monitoring, particularly in protected areas. Current learning-based detection systems depend heavily on camera sensor ability to capture UAVs in surveillance areas; however, advanced camera control methods remain limited. This paper proposes determining multi-camera trajectories that maximize UAV capture probability, ensuring UAVs remain within the camera field of view for further analysis, such as detection methods from camera-shot images. For this purpose, stochastic modeling is considered in the control framework for optimizing surveillance camera trajectories to enhance the probability of capturing UAVs. Key control parameters are derived through classical probability evaluations of the model with maximizing the entropy and covering trajectory-based strategies are applied. The reliability of stochastic system modeling is empirically validated through comprehensive computational experiments. These findings demonstrate the model potential to enhance UAV capture rates through optimized camera trajectories and coverage efficiency, paving the way for future advancements in real-environment applications.
KSP Keywords
Camera field of view, Camera sensor, Capture probability, Classical probability, Coverage efficiency, Detection Method, Detection Systems(IDS), Field of View(FoV), Learning-based, Model potential, Multi-camera
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
CC BY