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Journal of Vcibration Testing and System Dynamics 3(4) (2019) 469--480 | DOI:10.5890/JVTSD.2019.12.005

Liang Yu$^{1}$,$^{2}$, Yongchun Liu$^{3}$, Da Lin$^{4}$

$^{1}$ School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin, 644000, P.R. China

$^{2}$ Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering, Yibin, 644000, P.R. China

$^{3}$ School of Physics & Electronics Engineering, Sichuan University of Science & Engineering, Yibin, 644000, P.R. China

$^{4}$ School of Information Engineering, Xuzhou University of Technology, Xuzhou, 221000, P.R. China

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Abstract

In this paper, we present the search problem formulated as a decision making problem, the search agent decides whether the target is present in the search region, and if so, where it is located. Then we propose a sequential decision-making framework for a search agent to find a lost target within a bounded region with the searcher motion constraints and imperfect observations being considered. This framework enables the theoretical study to the evolution of the search decision, then we propose two effective adaptive search strategies, which have the advantage of requiring less computation than traditional search strategy. Simulation results shows that the proposed adaptive search strategies have a better performance. Finally, the proposed control strategies are analyzed from different perspectives in detail.

Acknowledgments

This work is supported by National Natural Science Foundation of China (No. 61640223), the Open Research Project from SKLMCCS (No. 20160106), Sichuan Provincial Natural Science Foundation (No. 2016JY0179), and The Key Project of Artificial Intelligence Key Laboratory of Sichuan Province (No. 2016RZJ02), the Innovation Fund of Postgraduate, Sichuan University of Science & Engineering (No. y2018042), Xuzhou Engineering College Cultivation Project (XKY2018126).

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