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Formation control is an important part of any system that utilizes multiple mobile agents to achieve its parti‐ cular goals. One of those applications is the mobile wi‐ reless network sensor. This field has become increasingly more popular in recent times due to the advancement of technology, especially in the fields of miniaturization and telecommunications. The main problem of this research is the relatively untested sensing capability of a mobile wireless sensor network in an operating area that has dis‐ tributed and/or multiple locations of high interest. The purpose of this research is to discover the compatibility of a multiple‐agent coverage control system with several examples of interest functions that have multiple and/or distributed points of global maximum value in order to explore more thoroughly the performance of a given sy‐ stem in a varying environments.
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Tom
Strony
74--80
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
autor
- Universitas Gadjah Mada, Yogyakarta, Indonesia
autor
- Universitas Gadjah Mada, Yogyakarta, Indonesia
autor
- Universitas Gadjah Mada, Yogyakarta, Indonesia
Bibliografia
- [1] T. M. Cheng and A. V. Savkin, “Decentralized control of a mobile sensor network for deployment in corridor coverage”. In: Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009, pp. 7897–7902, 10.1109/CDC.2009.5400065.
- [2] T. M. Cheng and A. V. Savkin, “Decentralized coordinated control of a vehicle network for deployment in sweep coverage”. In: 2009 IEEE International Conference on Control and Automation, 2009, pp. 275–279, 10.1109/ICCA.2009.5410535.
- [3] J. Cortes, S. Martinez, T. Karatas, and F. Bullo, “Coverage control for mobile sensing networks”. In: Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), vol. 2, Washington, DC, USA, 2002, pp. 1327–1332, 10.1109/ROBOT.2002.1014727.
- [4] P. Dames and V. Kumar, “Autonomous Localization of an Unknown Number of Targets Without Data Association Using Teams of Mobile Sensors”. In: IEEE Transactions on Automation Science and Engineering, vol. 12, no. 3, 2015, pp. 850–864, 10.1109/TASE.2015.2425212.
- [5] T. Elmokadem, “Distributed coverage control for robotic sensor networks in 3d sensing fields: Barrier and sweeping problems”. In: 2019 Chinese Control Conference (CCC), 2019, pp. 6088–6093, 10.23919/ChiCC.2019.8865256.
- [6] X. Han, L. Ma, and K. Feng, “Distributed coverage control of networked heterogeneous robots”. In: 2017 6th Data Driven Control and Learning Systems (DDCLS), Chongqing, China, 2017, pp. 286–291, 10.1109/DDCLS.2017.8068084.
- [7] I. I. Hussein and D. M. Stipanovic, “Effective Coverage Control for Mobile Sensor Networks With Guaranteed Collision Avoidance”. In: IEEE Transactions on Control Systems Technology, vol. 15, no. 4, 2007, pp. 642–657, 10.1109/TCST.2007.899155.
- [8] X. Jing, C. Fei, and X. Linying, “Event‑triggered coverage control for continuous‑time multi‑agent systems”. In: 2015 34th Chinese Control Conference (CCC), Hangzhou, China, 2015, pp. 1303–1308, 10.1109/ChiCC.2015.7259822.
- [9] M. Khaledyan, A. P. Vinod, M. Oishi, and J. A. Richards, “Optimal Coverage Control and Stochastic Multi‑Target Tracking”. In: 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019, pp. 2467–2472, 10.1109/CDC40024.2019.9029307.
- [10] S. Lloyd, “Least squares quantization in PCM”. In: IEEE Transactions on Information Theory, vol. 28, no. 2, 1982, pp. 129–137, 10.1109/TIT.1982.1056489.
- [11] C. Y. T. Ma, D. K. Y. Yau, N. K. Yip, N. S. V. Rao, and J. Chen, “Stochastic Steepest Descent Optimization of Multiple‑Objective Mobile Sensor Coverage”. In: IEEE Transactions on Vehicular Technology, vol. 61, no. 4, 2012, pp. 1810–1822, 10.1109/TVT.2012.2189591.
- [12] Y. Nakai and H. Ichihara, “Coverage control of mobile robots with adaptive gradient”. In: 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), Kanazawa, 2017, pp. 1016–1017, 10.23919/SICE.2017.8105446.
- [13] M. Naruse, K. Sekiguchi, and K. Nonaka, “Coverage Control for Multi‑Copter with Avoidance of Local Optimum and Collision Using Change of the Distribution Density Map”. In: 2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), Nara, 2018, pp. 1116–1121, 10.23919/SICE.2018.8492606.
- [14] M. Santos, S. Mayya, G. Notomista, and M. Egerstedt, “Decentralized Minimum‑Energy Coverage Control for Time‑Varying Density Functions”. In: 2019 International Symposium on Multi‑Robot and Multi‑Agent Systems (MRS), New Brunswick, NJ, USA, 2019, pp. 155–161, 10.1109/MRS.2019.8901076.
- [15] A. Shamshirgaran and F. Abdollahi, “Dynamic coverage control via underactuated autonomous underwater vehicles in unknown 3D environment”. In: 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA), Qazvin, Iran, 2016, pp. 333–338, 10.1109/ICCIAutom.2016.7483184.
- [16] R. Wang, W. Wan, X. Ma, and Y. Li, “Cloud model‑based control strategy on cluster communication coverage for wireless sensor networks”. In: 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), vol. 1, 2010, pp. 307–310, 10.1109/CAR.2010.5456840.
- [17] Y. Wang and I. I. Hussein, “Awareness Coverage Control Over Large‑Scale Domains With Intermittent Communications”. In: IEEE Transactions on Automatic Control, vol. 55, no. 8, 2010, pp. 1850–1859, 10.1109/TAC.2010.2042346.
- [18] J. Xiao, L. Sun, and S. Zhang, “Distance optimization based coverage control algorithm in mobile sensor network”. In: 2008 IEEE International Conference on Systems, Man and Cybernetics, 2008, pp. 3321–3325, 10.1109/ICSMC.2008.4811809.
- [19] K. Yang and X. Wang, “Team‑Based Blanket Coverage Control for Heterogeneous Multi‑agent Systems”. In: 2020 39th Chinese Control Conference (CCC), Shenyang, China, 2020, pp. 759–764, 10.23919/CCC50068.2020.9189045.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8b1a415e-c1a1-43ca-9f69-19ddba1c46c4