Abstract
Performing repeatable duties automatically was the dreams of human being for centuries. Although full autonomy has long been dreamed of by visionaries, many researches have been performed for surface vehicles automation since the last century to get close to this dream stepwise. To increase daily working hours and accuracy and reduce cost, operations such as hydrography are susceptible for autonomy. Beside platform topology, installed sensors and energy resources, the core elements of any autonomous surface vehicle are navigation, guidance and control systems. To perform bathymetry operation in autonomy manner, a reliable and robust navigation algorithm is designed and embedded in an autonomous surface vehicle titled Morvarid. Morvarid is a plug-in hybrid solar powered catamaran boat. The developed algorithm is a combination of extended Kalman filter, search ball and potential field approaches. Many experimental field tests are carried out after simulation in Simulink environment. Test results illustrated the algorithm and improved the path followed by reducing SD and RMSE and there is a good correlation between simulation run and experimental tests.
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Bertaska, I.R., Shah, B., von Ellenrieder, K., Švec, P., Klinger, W., Sinisterra, A.J., Dhanak, M. and Gupta, S.K., 2015. Experimental evaluation of automatically-generated behaviors for USV operations, Ocean Engineering, 106, 496–514.
Bibuli, M., Bruzzone, G., Caccia, M. and Lapierre, L., 2009. Path-following algorithms and experiments for an unmanned surface vehicle, Journal of Field Robotics, 26(8), 669–688.
Caccia, M., Bibuli, M., Bono, R. and Bruzzone, G., 2008. Basic navigation. guidance and control of an unmanned surface vehicle, Autonomous Robots, 25(4), 349–365.
Campbell, S., Naeem, W. and Irwin, G.W., 2012. A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres, Annual Reviews in Control, 36(2), 267–283.
Chaos, D., Moreno, D., Aranda, J. and de la Cruz, J.M., 2009. A realtime control for path following of an USV, IFAC Proceedings Volumes, 42(18), 261–266.
Do, K.D., Jiang, Z.P. and Pan J., 2004. Robust adaptive path following of underactuated ships, Automatica, 40(6), 929–944.
Dong, W.J. and Guo, Y., 2005. Nonlinear tracking control of under-actuated surface vessel, Proceedings of the 2005, American Control Conference, IEEE, Portland, OR, USA.
Dong, Z.P, Wan, L., Li, Y.M., Liu, T. and Zhang, G.C., 2015. Trajectory tracking control of underactuated USV based on modified back-stepping approach, International Journal of Naval Architecture and Ocean Engineering, 7(5), 817–832.
Fossen, T.I., 1994. Guidance and Control of Ocean Vehicles, John Wiley and Sons, Chichester, New York.
Fossen, T.I., 2011. Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons Ltd, Hoboken, NJ.
Giordano, F., Mattei, G., Parente, C., Peluso, F. and Santamaria, R., 2015. Integrating sensors into a marine drone for bathymetric 3D surveys in shallow waters, Sensors, 16(1), 41.
Gomez-Gil, J., Ruiz-Gonzalez, R., Alonso-Garcia, S. and Gomez-Gil, F.J., 2013. A Kalman Filter implementation for precision improvement in low-cost GPS positioning of tractors, Sensors, 13(11), 15307–15323.
Goodrich, M.A., 2002. Potential Fields Tutorial, Class Notes. https://doi.org/pdfs.semanticscholar.org/725e/fa1af22f41dcbecd8bd445ea82679a6eb7c6.pdf
Kjerstad, Ø.K., 2009. Dynamic Positionin Concepts for Unmanned Surface Vehicles, Master thesis in Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim.
Liu, Y.C. and Bucknall, R., 2015. Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment, Ocean Engineering, 97, 126–144.
Liu, Y.C. and Bucknall, R., 2016. The angle guidance path planning algorithms for unmanned surface vehicle formations by using the fast marching method, Applied Ocean Research, 59, 327–344.
Liu, Y.C. and Bucknall, R., 2018. Efficient multi-task allocation and path planning for unmanned surface vehicle in support of ocean operations, Neurocomputing, 275, 1550–1566.
Liu, Z.X., Zhang, Y.M., Yu, X. and Yuan, C., 2016. Unmanned surface vehicles: an overview of developments and challenges, Annual Reviews in Control, 41, 71–93.
Ma, Y.L., 2015. Two modified unscented Kalman filter and acceleration information in unmanned surface vehicle estimation, IFAC-PapersOnLine, 48(28), 1450–1455.
Más, F.R., Zhang, Q. and Hansen, A.C., 2010. Mechatronics and Intelligent Systems for Off-Road Vehicles, Springer, London, pp. 62–65.
Mousazadeh, H., Hamid, J., Elham, O., Farshid, M., Ali, K., Yousef, S.Z. and Ashkan, M., 2017. Experimental evaluation of a hydrography surface vehicle in four navigation modes, Journal of Ocean Engineering and Science, 2(2), 127–136.
Mousazadeh, H., Jafarbiglu, H., Abdolmaleki, H., Omrani, E., Monhaseri, F., Abdollahzadeh, M.R., Mohammadi-Aghdam, A., Kiapei, A., Salmani-Zakaria, Y. and Makhsoos, A., 2018. Developing a navigation. guidance and obstacle avoidance algorithm for an Unmanned Surface Vehicle (USV) by algorithms fusion, Ocean Engineering, 159, 56–65.
Muske, K.R., Ashrafiuon, H., Haas, G., McCloskey, R. and Flynn, T., 2008. Identification of a control oriented nonlinear dynamic USV model, Proceedings of 2008 American Control Conference, IEEE, Seattle, WA, USA.
Naeem, W., Henrique, S.C. and Hu, L., 2016. A reactive COLREGs-Compliant navigation strategy for autonomous maritime navigation, IFAC-PapersOnLine, 49(23), 207–213.
Naeem, W., Sutton, R. and Xu, T., 2012. An integrated multi-sensor data fusion algorithm and autopilot implementation in an uninhabited surface craft, Ocean Engineering, 39, 43–52.
Naeem, W., Xu, T., Sutton, R. and Tiano, A., 2008. The design of a navigation. guidance, and control system for an unmanned surface vehicle for environmental monitoring, Journal of Engineering for the Maritime Environment, 222(2), 67–79.
Peng, Y., Yang, Y., Cui, J.X., Li, X.M., Pu, H.Y., Gu, J.S., Xie, S.R. and Luo, J., 2017. Development of the USV ‘JingHai-I’ and sea trials in the Southern Yellow Sea, Ocean Engineering, 131, 186–196.
Pêtrès, C., Romero-Ramirez, M.A. and Plumet, F., 2012. A potential field approach for reactive navigation of autonomous sailboats, Robotics and Autonomous Systems, 60(12), 1520–1527.
Qin, Z.H., Lin, Z., Yang, D.M. and Li, P., 2017. A task-based hierarchical control strategy for autonomous motion of an unmanned surface vehicle swarm, Applied Ocean Research, 65, 251–261.
Reyhanoglu, M., 1996. Control and stabilization of an underactuated surface vessel, Proceedings of the 35th IEEE Conference on Decision and Control, IEEE, Kobe, Japan.
Rodriguez, M. and Gómez, J., 2009. Analysis of three different Kalman filter implementations for agricultural vehicle positioning, The Open Agriculture Journal, 3, 13–19.
Simetti, E., Turetta, A., Torelli, S. and Casalino, G., 2012. Civilian harbour protection: Interception of suspect vessels with unmanned surface vehicles, IFAC Proceedings Volumes, 45(27), 435–440.
Tang, P.P., Zhang, R.B., Liu, D.L., Huang, L.H., Liu, G.Q. and Deng, T.Q., 2015. Local reactive obstacle avoidance approach for high-speed unmanned surface vehicle, Ocean Engineering, 106, 128–140.
Acknowledgment
The authors would like to acknowledge the Ports and Maritime Organization for funding the Morvarid Project No. 20S/7509. 2015.
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Foundation item: The study was financially supported by the Ports and Maritime Organization for funding the Morvarid Project (Grant No. 20S/7509. 2015).
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Mousazadeh, H., Kiapey, A. Experimental Evaluation of A New Developed Algorithm for An Autonomous Surface Vehicle and Comparison with Simulink Results. China Ocean Eng 33, 268–278 (2019). https://doi.org/10.1007/s13344-019-0026-4
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DOI: https://doi.org/10.1007/s13344-019-0026-4