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Abstract: A novel controller for finding the best communication point is proposed for collecting data from a seabed platform by a single unmanned surface vehicle (USV) using underwater acoustic communication (UAC). As far as we know, extremum seeking based on climbing control is usually implemented by multiple vehicles or agents because of the large range of measurement and easy acquisition of gradient estimation. A single vehicle cannot rapidly estimate the field because of the limited extent for measurement; therefore, it is difficult for a single vehicle to seek the extremum point in a field. In this study, an oscillation motion (OM) is designed for a single USV to acquire UAC’s link strength data between the seabed platform and the USV. The field for UAC’s link strength is updated using new measurement from an OM of the USV based on a multi-variable weight linear iteration method. A controller for seeking the best UAC’s point of the USV is designed using gradient climbing and artificial potential considering iterative estimation of an unknown field and an OM operation, and the stability is proved. The reliability and efficiency are shown in simulation results.

一种用于寻找无人船回收海床基数据最佳通信点的梯度上升控制法

[1]Bachmayer R, Leonard NE, 2002. Vehicle networks for gradient descent in a sampled environment. Proc 41^st IEEE Conf on Decision and Control, p.112-117.

[2]Bingham B, Kraus N, Howe B, et al., 2012. Passive and active acoustics using an autonomous wave glider. J Field Robot, 29(6):911-923.

[3]Biyik E, Arcak M, 2008. Gradient climbing information via extremum seeking and passivity-based coordination rules. Asian J Contr, 10(2):201-211.

[4]Brown H, Jenkins L, Meadows G, et al., 2010. BathyBoat: an autonomous surface vessel for stand-alone survey and underwater vehicle network supervision. Mar Technol Soc J, 44(4):20-29.

[5]Choi J, Oh S, Horowitz R, 2009. Distributed learning and cooperative control for multi-agent systems. Automatica, 45(12):2802-2814.

[6]Curcio J, Leonard J, Vaganay J, et al., 2005. Experiments in moving baseline navigation using autonomous surface craft. IEEE Conf on OCEANS, p.730-735.

[7]Gao B, Li HB, Li W, et al., 2016. 3D Moth-inspired chemical plume tracking and adaptive step control strategy. Adapt Behav, 24(1):52-65.

[8]Han GJ, Li SS, Zhu CS, et al., 2017. Probabilistic neighborhood-based data collection algorithms for 3D underwater acoustic sensor networks. Sensors, 17(2):316.

[9]Hollinger GA, Choudhary S, Qarabaqi P, et al., 2012. Underwater data collection using robotic sensor networks. IEEE J Sel Areas Commun, 30(5):899-911.

[10]Jin JC, Zhang J, Lv ZC, et al., 2016. Active and passive underwater acoustic application using an unmanned surface vehicle. IEEE Conf on OCEANS, p.1-6.

[11]Khong SZ, Tan Y, Manzie C, et al., 2015. Extremum seeking of dynamical systems via gradient descent and stochastic approximation methods. Automatica, 56:44-52.

[12]Lawson RA, Graham D, Stalin S, et al., 2012. The next generation Easy-to-Deploy (ETD) tsunami assessment buoy. IEEE Conf on OCEANS, p.1-8.

[13]Martins R, de Sousa JB, Afonso CC, et al., 2011. REP10 AUV: shallow water operations with heterogeneous autonomous vehicles. IEEE Conf on OCEANS, p.1-6.

[14]Matos A, Silva E, Cruz N, et al., 2013. Development of an unmanned capsule for large-scale maritime search and rescue. IEEE Conf on OCEANS, p.1-8.

[15]Murphy C, Walls JM, Schneider T, et al., 2014. CAPTURE: a communications architecture for progressive transmission via underwater relays with eavesdropping. IEEE J Ocean Eng, 39(1):120-130.

[16]Nađ Đ, Mišković N, Mandić F, 2015. Navigation, guidance and control of an overactuated marine surface vehicle. Ann Rev Contr, 40:172-181.

[17]Naeem W, Xu T, Sutton R, et al., 2008. The design of a navigation, guidance, and control system for an unmanned surface vehicle for environmental monitoring. Proc Inst Mech Eng M-J Eng Mar Environ, 222(2):67-79.

[18]Ögren P, Fiorelli E, Leonard NE, 2004. Cooperative control of mobile sensor networks: adaptive gradient climbing in a distributed environment. IEEE Trans Automat Contr, 49(8):1292-1302.

[19]Park JH, Kang MJ, Kim TY, et al., 2017. Development of an unmanned surface vehicle system for the 2014 Maritime RobotX Challenge. J Field Robot, 34(4):644-665.

[20]Reed BL, Leighton J, Stojanovic M, et al., 2016. Multi-vehicle dynamic pursuit using underwater acoustics. In: Inaba M, Corke P (Eds.), Robotics Research. Springer Tracts in Advanced Robotics. Springer Press, Berlin, Germany, p.79-94.

[21]Santos N, Matos A, Cruz N, 2008. Navigation of an autonomous underwater vehicle in a mobile network. IEEE Conf on OCEANS, p.1-5.

[22]Sinisterra AJ, Dhanak MR, von Ellenrieder K, 2017. Stereovision-based target tracking system for USV operations. Ocean Eng, 133:197-214.

[23]Stojanovic M, 2006. On the relationship between capacity and distance in an underwater acoustic communication channel. Proc 1^st ACM Int Workshop on Underwater Networks, p.41-47.

[24]Stojanovic M, Freitag L, 2013. Recent trends in underwater acoustic communications. Mar Technol Soc J, 47(5):45- 50.

[25]Stojanovic M, Preisig J, 2009. Underwater acoustic communication channels propagation models and statistical characterization. IEEE Commun Mag, 47(1):84-89.

[26]Suzuki N, Kitajima H, Kaba H, et al., 2015. An experiment of real-time data transmission of sonar images from cruising UUV to distant support vessel via USV: development of underwater real-time communication system (URCS) by parallel cruising. IEEE Conf on OCEANS, p.1-6.

[27]Zhang FM, Leonard NE, 2010. Cooperative filters and control for cooperative exploration. IEEE Trans Autom Contr, 55(3):650-663.

[28]Zhou FQ, Lu XD, 2009. Theory of Optimal Estimation. Higher Education Press, Beijing, China, p.16-19 (in Chinese).