Metacognitive Decision-Making Framework for Multi-UAV Target Search Without Communication

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Metacognitive Decision-Making Framework for Multi-UAV Target Search Without Communication
Title:
Metacognitive Decision-Making Framework for Multi-UAV Target Search Without Communication
Journal Title:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Publication Date:
09 February 2024
Citation:
Senthilnath, J., Harikumar, K., & Sundaram, S. (2024). Metacognitive Decision-Making Framework for Multi-UAV Target Search Without Communication. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 1–12. https://doi.org/10.1109/tsmc.2024.3358060
Abstract:
This article presents a metacognitive decision-making (MDM) framework inspired by human-like metacognitive principles. The MDM framework is incorporated in unmanned aerial vehicles (UAVs) deployed for decentralized stochastic search without communication for detecting and confirming stationary targets (fixed/sudden pop-up) and dynamic targets. The UAVs are equipped with multiple sensors (varying sensing capability) and search for targets in a largely unknown area. The MDM framework consists of a metacognitive component and a self-cognitive component. The metacognitive component helps to self-regulate the search with multiple sensors addressing the issues of “which-sensor-to-use”, “when-to-switch-sensor”, and “how-to-search.” Based on the information gathered by sensors carried by each UAV, the self-cognitive component regulates different levels of stochastic search and switching levels for effective searching, where the lower levels of search aim to localize a target (detection) and the highest level of a search exploit a target (confirmation). The performance of the MDM framework with two sensors having a low accuracy for detection and increased accuracy to confirm targets is evaluated through Monte Carlo simulations and compared with six decentralized multi-UAV search algorithms (three self-cognitive searches and three self and social-cognitive-based searches). The results indicate that the MDM framework can efficiently detect and confirm targets in an unknown environment.
License type:
Publisher Copyright
Funding Info:
There was no specific funding for the research done
Description:
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
2168-2232
2168-2216
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