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Survey on Communication and Networks for Autonomous Marine Systems

  • Artur Zolich
  • David Palma
  • Kimmo Kansanen
  • Kay Fjørtoft
  • João Sousa
  • Karl H. Johansson
  • Yuming Jiang
  • Hefeng Dong
  • Tor A. Johansen
Open Access
Article
  • 378 Downloads

Abstract

The rapid development of autonomous systems and Information and Communications Technologies (ICT) create new opportunities for maritime activities. Existing autonomous systems are becoming more powerful and utilise the capabilities of several types of devices such as Autonomous Underwater Vehicles (AUVs), Unmanned Surface Vehicles (USVs) – sometimes referred as Autonomous Surface Vehicles (ASVs) –, Unmanned Aerial Vehicles (UAVs), moored and drifting systems and, recently emerging, autonomous vessels. Their importance in providing new services in maritime environments is undeniable and the opportunity for coordinated and interconnected operations is clear. However, continuous wide integration of various technologies in maritime environments still faces many challenges. Operations may take place in remote locations, so that dependence on third-party infrastructures such as satellite communication or terrestrial communication systems must be expected. The reliability, performance, availability, and cost of such systems are important issues that need to be tackled. This work reviews the major advancements on state-of-the-art autonomous maritime vehicles and systems, which are used in several different scenarios, from scientific research to transportation. Moreover, the paper highlights how available technologies can be composed in order to efficiently and effectively operate in maritime environments. Highlights of the trade-off between autonomy and communication requirements are provided and followed by an overview of promising communication and networking technologies that could encourage the integration of autonomous systems in maritime scenarios.

Keywords

Marine technology Autonomous vehicles Oceanographic techniques Communication systems Computer networks 

Notes

Acknowledgements

This work was partially funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 699924.

The Research Council of Norway is acknowledged as the main sponsor of NTNU AMOS (Centre for Autonomous Marine Operations and Systems), grant number 223254, and the project Hybrid Operations in Maritime Environments (HOME) funded by the MAROFF programme, grant number 269480.

The work has been supported by the light house project CAMOS of the Faculty of Information Technology and Electrical Engineering, NTNU.

References

  1. 1.
    Campbell, N.: Biology: Concepts & Connections. Pearson/Benjamin Cummings (2006), https://books.google.com.ng/books?id=OhdFAQAAIAAJ
  2. 2.
    European Union: The blue economy of the european union. http://ec.europa.eu/maritimeaffairs/documentation/publications/documents/poster-blue-growth-2015_en.pdf (2015), [Online; Accessed 13 Jul 2016]
  3. 3.
    Woodget, A.S., Carbonneau, P.E., Visser, F., Maddock, I.P.: Quantifying submerged fluvial topography using hyperspatial resolution uas imagery and structure from motion photogrammetry. Earth Surface Process Landforms 40(1), 47–64 (2015).  https://doi.org/10.1002/esp.3613 CrossRefGoogle Scholar
  4. 4.
    Sivertsen, A., Solbø, S., Storvold, R., Tøllefsen, A., Johansen, K.S.: Automatic mapping of sea ice using unmanned aircrafts. In: ReCAMP Flagship Workshop Book of Abstracts. p. 30. ReCAMP Flagship Workshop, ReCAMP Flagship Workshop (2016), n/aGoogle Scholar
  5. 5.
    Lucieer, A., Turner, D., King, D.H., Robinson, S.A.: Using an unmanned aerial vehicle (uav) to capture micro-topography of antarctic moss beds. Int. J. Applied Earth Observ. Geoinform. Part A 27, 53–62 (2014). http://www.sciencedirect.com/science/article/pii/S0303243413000603 special Issue on Polar Remote Sensing (2013)CrossRefGoogle Scholar
  6. 6.
    Solbø, S., Storvold, R., Sivertsen, A., Petrich, C., Sand, B.: Imaging sea ice structure by small remotely piloted aircraft. In: ReCAMP Flagship Workshop Book of Abstracts. p. 32. ReCAMP Flagship Workshop, ReCAMP Flagship Workshop (2016), n/aGoogle Scholar
  7. 7.
    Faria, M., Pinto, J., Py, F., Fortuna, J., Dias, H., Martins, R., Leira, F., Johansen, T.A., Sousa, J., Rajan, K.: Coordinating uavs and auvs for oceanographic field experiments: Challenges and lessons learned experiments in uav and auv control for coastal oceanography. In: IEEE Int. Conf. Robotics and Automation. Hong Kong (2014)Google Scholar
  8. 8.
    Ludvigsen, M., Dias, P.S., Ferreira, S., Fossum, T.O., Hovstein, V., Johansen, T.A., Krogstad, T.R., Midtgaard, Ø., Norgren, P., J.S., Sture, Ø., Vågsholm, E., Zolich, A.: Autonomous network of heterogeneous vehicles for marine research and management. In: IEEE Oceans 2016 – Monterey (2016)Google Scholar
  9. 9.
    Py, F., Pinto, J., Silva, M.A., Johansen, T.A., Sousa, J., K., R.: Europtus: A mixed-initiative controller for multi-vehicle oceanographic field experiments. In: Int. Symp. Experimental Robotics (2016)Google Scholar
  10. 10.
    Roemmich, D., Boehme, L., Claustre, H., Freeland, H., Fukasawa, M., Goni, G., Gould, W.J., Gruber, N., Hood, M., Kent, E., Lumpkin, R., Smith, S., Testor, P.: Integrating the ocean observing system: Mobile platforms. In: Proceedings of OceanObs’09: Sustained Ocean Observations and Information for Society. European Space Agency (2010)  https://doi.org/10.5270/OceanObs09.pp.33
  11. 11.
    Greene, C.H., Meyer-Gutbrod, E.L., McGarry, L.P. Jr., L.C.H., McClatchie, S., Packer, A., Jung, J.B., Acker, T., Dorn, H., Pelkie, C.: A wave glider approach to fisheries acoustics: Transforming how we monitor the nation’s commercial fisheries in the 21st century. Oceanography 27.  https://doi.org/10.5670/oceanog.2014.82 (2014)
  12. 12.
    Perry, M.J., Rudnick, D.L.: Observing the ocean with autonomous and lagrangian platforms and sensors: The role of alps in sustained ocean observing systems. Oceanography 16(4), 31–36 (2003). n/aCrossRefGoogle Scholar
  13. 13.
    Dawson, C.: Arctic shipping volume rises as ice melts. http://www.wsj.com/articles/arctic-cargo-shipping-volume-is-rising-as-ice-melts-1414612143 (2014), [Online; Accessed 15 May 2016]
  14. 14.
    Trishchenko, A.P., Garand, L.: Continuous coverage of the arctic: Two-satellite highly elliptical orbit (heo) system is better than two dozen of leo polar orbiters, http://www.goes-r.gov/downloads/2012-Science-Week/posters/tues/13_Trishchenko.pdf
  15. 15.
    Imagenex Technologies: Overview of the imagenex deltat sonar real time operation in an autonomous underwater vehicle (auv) application (2006)Google Scholar
  16. 16.
    Johansen, T.A., Zolich, A., Hansen, T., Sørensen, A.J.: Unmanned aerial vehicle as communication relay for autonomous underwater vehicle - field tests. In: IEEE Globecom Workshop - Wireless Networking and Control for Unmanned Autonomous Vehicles. Austin (2014)Google Scholar
  17. 17.
    Zolich, A., Johansen, T.A., Cisek, K., Klausen, K.: Unmanned aerial system architecture for maritime missions. Design and hardware description. In: 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS). pp. 342–350 (2015)Google Scholar
  18. 18.
    Maritime, K.: Reshaping underwater operations – live footage of groundbreaking robotic subsea ‘snake’ released, https://www.km.kongsberg.com/ks/web/nokbg0238.nsf/AllWeb/81FA0DE33AE2C0FAC12580CA0037AD9C?OpenDocument
  19. 19.
    Sousa, L.L., López-Castejón, F., Gilabert, J., Relvas, P., Couto, A., Queiroz, N., Caldas, R., Dias, P.S., Dias, H., Faria, M., Ferreira, F., Ferreira, A.S., Fortuna, J., Gomes, R.J., Loureiro, B., Martins, R., Madureira, L., Neiva, J., Oliveira, M., Pereira, J., Pinto, J., Py, F., Queirós, H., Silva, D., Sujit, P., Zolich, A., Johansen, T.A., Sousa, J., Rajan, K.: Integrated monitoring of mola mola behaviour in space and time. PLoS ONE (2016)Google Scholar
  20. 20.
    Pinto, J., Dias, P.S., Martins, R., Fortuna, J., Marques, E., Sousa, J.: The lsts toolchain for networked vehicle systems. In: OCEANS - Bergen, 2013 MTS/IEEE. pp. 1–9 (June 2013)Google Scholar
  21. 21.
    Ocean, G.: Ocean tracking network global metadata and data atlas. http://members.oceantrack.org/data/discovery/GLOBAL.htm (2016), [Online; Accessed 13 July 2016]
  22. 22.
  23. 23.
    M., D.: Methods for the deployment and maintenance of an acoustic tag tracking array: An example from california’s channel islands. Mar. Technol. Soc. J. 39, 74–80 (2005)CrossRefGoogle Scholar
  24. 24.
    Beauchamp, N.: Return of the intrepid wave glider. http://oceantrackingnetwork.org/return-of-the-intrepid-wave-glider/ (2014), [Online; Accessed 13 July 2016]
  25. 25.
    Zolich, A., Skøien, K.R., Alfredsen, J.A., Johansen, T.A.: A communication bridge between underwater sensors and unmanned vehicles using a surface wireless sensor network – design and validation. In: IEEE Oceans Shanghai (2016)Google Scholar
  26. 26.
    Berge, J., Geoffroy, M., Johnsen, G., Cottier, F., Bluhm, B., Vogedes, D.: Ice-tethered observational platforms in the arctic ocean pack ice. IFAC-PapersOnLine 49(23), 494–499 (2016) http://www.sciencedirect.com/science/article/pii/S2405896316320742 CrossRefGoogle Scholar
  27. 27.
    Fossen, T.I.: Project 5 — autonomous aerial systems for marine monitoring and data collection. http://www.ntnu.edu/amos/project-5 (2016), [Online; Accessed 13 July 2016]
  28. 28.
    Ltd., H.A.V.: Access to the arctic: Time to try something different - press release (2013), https://www.hybridairvehicles.com/downloads/Airlander-220.pdf
  29. 29.
    DNV-GL: The revolt – a new inspirational ship concept (2015) https://www.dnvgl.com/technology-innovation/revolt/index.html
  30. 30.
    Rolls-Royce Marine: Rolls-royce drone ships challenge $375 billion industry: Freight (2014) http://www.bloomberg.com/news/articles/2014-02-25/rolls-royce-drone-ships-challenge-375-billion-industry-freight
  31. 31.
    Rolls-Royce: Rolls-royce unveils a vision of the future of remote and autonomous shipping. http://www.rolls-royce.com/media/press-releases/yr-2016/pr-12-04-2016-rr-unveils-a-vision-of-future-of-remote-and-autonomus-shipping.aspx (2016), [Online; Accessed 13 July 2016]
  32. 32.
    Rødseth, Ø.J., Kvamstad, B., Porathe, T., Burmeister, H.C.: Communication architecture for an unmanned merchant ship. In: IEEE Oceans. Bergen (2013)Google Scholar
  33. 33.
    Rolls-Royce Marine: Rolls-royce unveils a vision of the future of remote and autonomous shipping (2016) http://www.rolls-royce.com/media/press-releases/yr-2016/pr-12-04-2016-rr-unveils-a-vision-of-future-of-remote-and-autonomus-shipping.aspx
  34. 34.
    World, Y.B.: Finferries’ 65 metre double ended ferry, the stella will be used to test how crewless ships function in a real environment (2016) http://www.ybw.com/pictures/rolls-royce-crewless-smart-boats-18760/attachment/26248512775_8e66afa2b0_o
  35. 35.
    Elkins, L., Sellers, D., Monach, W.R.: The autonomous maritime navigation (amn) project: Field tests, autonomous and cooperative behaviors, data fusion, sensors and vehicles. J. Field Robot. 27, 790–818 (2010)CrossRefGoogle Scholar
  36. 36.
    Wolf, M.T., Assad, C., Kuwata, Y., Howard, A., Aghazarian, H., Zhu, D., Lu, T., Trebl-Ollennu, A., Huntsberger, T.: 360-degree visual detection and target tracking on an autonomous surface vehicle. J. Field Robot. 27, 819–830 (2010)CrossRefGoogle Scholar
  37. 37.
    Huntsberger, T., Aghazarian, H., Howard, A., Trotz, D.C.: Stereo vision-based navigation for autonomous surface vessels. J. Field Robot. 28, 3–18 (2011)CrossRefGoogle Scholar
  38. 38.
    Kuwata, Y., Wolf, M.T., Zarzhitsky, D., Huntsberger, T.L.: Safe maritime autonomous navigation with COLREGS, using velocity obstacles. IEEE J. Oceanic Eng. 39, 110–119 (2014)CrossRefGoogle Scholar
  39. 39.
    COLREGs - convention on the international regulations for preventing collisions at sea, international maritime organization (IMO) (1972)Google Scholar
  40. 40.
    Stensvold, T.: Rolls-royce bygger fjernstyringssenter i Ålesund (2017), https://www.tu.no/artikler/rolls-royce-bygger-fjernstyringssenter-i-alesund/377772
  41. 41.
    Turku, U.: Aawa — advanced autonomous waterborne applications initiative. https://www.utu.fi/en/units/law/research/research-projects/Pages/aawa.aspx (2015), [Online; Accessed 13 July 2016]
  42. 42.
    Hannu, K.: Rolls-royce and vtt unveil a vision of ship intelligence with futuristic ox bridge concept. http://www.vttresearch.com/media/news/rolls-royce-and-vtt-unveil-a-vision-of-ship-intelligence-with-futuristic-ox-bridge-concept (2014), [Online; Accessed 13 July 2016]
  43. 43.
    MUNIN Consortium: Research in maritime autonomous systems project results and technology potentials. http://www.unmanned-ship.org/munin/wp-content/uploads/2016/02/MUNIN-final-brochure.pdf (2016), [Online; Accessed 13 July 2016]
  44. 44.
    Johansen, T.A., Perez, T.: Unmanned aerial surveillance system for hazard collision avoidance in autonomous shipping. In: International Conference on Unmanned Aircraft Systems, Washington DC (2016)Google Scholar
  45. 45.
    Kongsberg: Collaboration on swimming robots for subsea maintenance. https://www.km.kongsberg.com/ks/web/nokbg0238.nsf/AllWeb/2800489E780D5865C1257F99002DCDA6?OpenDocument(2016), [Online; Accessed 13 July 2016]
  46. 46.
    Guerra, A.G., Francisco, F., Villate, J., Agelet, F.A., Bertolami, O., Rajan, K.: On small satellites for oceanography: A survey. Acta Astronautica 127, 404–423 (2016) http://www.sciencedirect.com/science/article/pii/S0094576515303441 CrossRefGoogle Scholar
  47. 47.
    Osse, T.J., Meinig, C., Stalin, S., Milburn, H.: The prawler, a vertical profiler powered by wave energy. In: OCEANS 2015 - MTS/IEEE Washington. pp. 1–8 (2015)Google Scholar
  48. 48.
    Domeier, M.L.: Methods for the deployment and maintenance of an acoustic tag tracking array: An example from california’s channel islands. Marine Technol Soc J 39(1), 74–80 (2005).  https://doi.org/10.4031/002533205787521668 CrossRefGoogle Scholar
  49. 49.
    Dunbabin, M., Grinham, A.: Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring. In: 2010 IEEE International Conference on Robotics and Automation. pp. 5268–5274 (2010)Google Scholar
  50. 50.
    Caccia, M., Bibuli, M., Bono, R., Bruzzone, G.: Basic navigation, guidance and control of an unmanned surface vehicle. Auton. Robot. 25, 349–365 (2008)CrossRefGoogle Scholar
  51. 51.
    Kimball, P., Bailey, J., Das, S., Geyer, R., Harrison, T., Kunz, C., Manganini, K., Mankoff, K., Samuelson, K., Sayre-McCord, T., Straneo, F., Traykovski, P., Singh, H.: The whoi jetyak: An autonomous surface vehicle for oceanographic research in shallow or dangerous waters. In: 2014 IEEE/OES Autonomous Underwater Vehicles (AUV). pp. 1–7 (2014)Google Scholar
  52. 52.
    Barbatei, R., Skavhaug, A., Johansen, T.A.: Acquisition and relaying of data from a floating wireless sensor node using an unmanned aerial vehicle. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 677–686 (2015)Google Scholar
  53. 53.
    Palmer, J., Yuen, N., Ore, J.P., Detweiler, C., Basha, E.: On air-to-water radio communication between uavs and water sensor networks. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 5311–5317 (2015)Google Scholar
  54. 54.
    Hovstein, V.E., Sægrov, A., Johansen, T.A.: Experiences with coastal and maritime UAS BLOS operation with phased-array antenna digital payload data link. In: Int. Conf. Unmanned Aerial Systems (ICUAS). Orlando (2014)Google Scholar
  55. 55.
    Sherman, J., Davis, R.E., Owens, W.B., Valdes, J.: The autonomous underwater glider “spray”. IEEE J. Ocean. Eng. 26(4), 437–446 (2001)CrossRefGoogle Scholar
  56. 56.
    O’Reilly, T.C., Kieft, B., Chaffey, M.: Communications relay and autonomous tracking applications for wave glider. In: OCEANS 2015 - Genova (2015)Google Scholar
  57. 57.
    Gizmag: Darpa readies unmanned actuv sub hunter for sea trials (2016), http://www.gizmag.com/darpa-actuv-unmanned-sub-hunter/41842/
  58. 58.
    Yuh, J.: Design and control of autonomous underwater robots: A survey. Auton. Robot. 8, 7–24 (2000)CrossRefGoogle Scholar
  59. 59.
    Zheng, H., Negenborn, R.R., Lodewijks, G.: Survey of approaches for improving the intelligence of marine surface vehicles. In: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013). pp. 1217–1223 (2013)Google Scholar
  60. 60.
    Fernandes, P.G., Stevenson, P., Brierley, A.S., Armstrong, F., Simmonds, E.: Autonomous underwater vehicles: future platforms for fisheries acoustics. ICES J Mar Sci 60(3), 684 (2003).  https://doi.org/10.1016/S1054-3139(03)00038-9 CrossRefGoogle Scholar
  61. 61.
    Cui, J.H., Kong, J., Gerla, M., Zhou, S.: The challenges of building mobile underwater wireless networks for aquatic applications. IEEE Netw 20(3), 12–18 (2006)CrossRefGoogle Scholar
  62. 62.
    Rajan, K., Py, F.: T-rex: Partitioned inference for auv mission control. In: Further Advances in Unmanned Marine Vehicles. pp. 171–199. Control, Robotics & Sensors, Institution of Engineering and Technology (2012), http://digital-library.theiet.org/content/books/10.1049/pbce077e_ch9
  63. 63.
    Vasilescu, I., Kotay, K., Rus, D., Dunbabin, M., Corke, P.: Data collection, storage, and retrieval with an underwater sensor network. In: Proceedings of the International Conference on Embedded Networked Sensor Systems (ACM) SenSys 2005 (2005)Google Scholar
  64. 64.
    Desa, E., Maurya, P.K., Pereira, A., Pascoal, A.M., Prabhudesai, R.G., Mascarenhas, A., Desa, E., Madhan, R., Matondkar, S.G.P., Navelkar, G., Prabhudesai, S., Afzulpurkar, S.: A small autonomous surface vehicle for ocean color remote sensing. IEEE J. Ocean. Eng. 32(2), 353–364 (2007)CrossRefGoogle Scholar
  65. 65.
    Manley, J.E.: Unmanned surface vehicles, 15 years of development. In: IEEE/MTS Oceans. Quebec City (2008)Google Scholar
  66. 66.
    Offshore-technology.com: Using autonomous vehicles to track ice in iceberg alley (2015), http://www.offshore-technology.com/
  67. 67.
    Hine, R., Willcox, S., Hine, G., Richardson, T.: The wave glider: A wave-powered autonomous marine vehicle. In: OCEANS 2009, pp. 1–6 (2009)Google Scholar
  68. 68.
    Global, A.: Asv global world leading marine autonomy (2017), http://asvglobal.com/
  69. 69.
    Norgren, P., Ludvigsen, M., Ingebretsen, T., Hovstein, V.E.: Tracking and remote monitoring of an autonomous underwater vehicle using an unmanned surface vehicle in the trondheim fjord. In: OCEANS 2015 - MTS/IEEE Washington. pp. 1–6 (2015)Google Scholar
  70. 70.
    Djapic, V., Na: Collaborative autonomous vehicle use in mine countermeasures. Sea Technology Magazine (2010) http://www.sea-technology.com/features/2010/1110/autonomous_vehicle.php
  71. 71.
    Zhang, J., Xiong, J., Zhang, G., Gu, F., He, Y.: Flooding disaster oriented usv uav system development demonstration. In: OCEANS 2016 - Shanghai, pp. 1–4 (2016)Google Scholar
  72. 72.
    Mendonça, R., Marques, M.M., Marques, F., Lourenço, A., Pinto, E., Santana, P., Coito, F., Lobo, V., Barata, J.: A cooperative multi-robot team for the surveillance of shipwreck survivors at sea. In: OCEANS 2016 MTS/IEEE Monterey, pp. 1–6 (2016)Google Scholar
  73. 73.
    Fan, Y., Ma, J., Wang, G., Li, T.: Design of a heterogeneous marsupial robotic system composed of an usv and an uav. In: 2016 Eighth International Conference on Advanced Computational Intelligence (ICACI), pp. 395–399 (2016)Google Scholar
  74. 74.
    Warwick, G.: Hybrid vtol uavs – back to the future. http://aviationweek.com/blog/hybrid-vtol-uavs-back-future (2014), [Online; Accessed 13 July 2016]
  75. 75.
    Sarda, E.I., Dhanak, M.R.: A usv-based automated launch and recovery system for auvs. IEEE J. Ocean. Eng. 42(1), 37–55 (2017)Google Scholar
  76. 76.
    de Sousa, J.B., McGuillivary, P., Vicente, J., Bento, M.N., Morgado, J.A.P., Matos, M.M., Bencatel, R.A.G., de Oliveira, P.M.: Handbook of Unmanned Aerial Vehicles, chap. Unmanned Aircraft Systems for Maritime Operations, pp. 2787–2811. Springer, Netherlands (2015)CrossRefGoogle Scholar
  77. 77.
    Usbeck, K., Gillen, M., Loyall, J., Gronosky, A., Sterling, J., Kohler, R., Newkirk, R., Canestrare, D.: Data ferrying to the tactical edge: A field experiment in exchanging mission plans and intelligence in austere environments. In: 2014 IEEE Military Communications Conference, pp. 1311–1317 (2014)Google Scholar
  78. 78.
    Chamberlain, L., Scherer, S.: Robocopters to the rescue. IEEE Spectr. 50(10), 28–33 (2013)CrossRefGoogle Scholar
  79. 79.
    Parasuraman, R., Sheridan, T.B., Wickens, C.D.: A model for types and levels of human interaction with automation. IEEE Trans. Syst. Man, Cybern.- Part A: Syst. Humans 30(3), 286–297 (2000)CrossRefGoogle Scholar
  80. 80.
    Register, L.: Shipright design and constructin, additional design procedures: Lr code for unmanned marine systems. Tech. rep., Lloyd’s Register Group Limited (2 2017), http://www.lr.org/en/services/unmanned-code.aspx
  81. 81.
    Council, N.R.: Review of ONR’s Uninhabited Combat Air Vehicles Program. National Academies Press, Washington DC (2000)Google Scholar
  82. 82.
    International, S.: U.S. department of transportation’s new policy on automated vehicles adopts sae international’s levels of automation for defining driving automation in on-road motor vehicles (1 2014) https://www.sae.org/news/3544/
  83. 83.
    Zolich, A., Johansen, T.A., Sægrov, A., Vågsholm, E., Hovstein, V.: Coordinated maritime missions of unmanned vehicles - network architecture and performance analysis. In: IEEE ICC, Mobile and Wireless Networking. Paris (2017)Google Scholar
  84. 84.
    Grancharova, A., Grøtli, E.I., Ho, D.T., Johansen, T.A.: UAVs, trajectory planning by distributed MPC under radio communication path loss constraints. J. Intell. Robot. Syst. 79, 115–134 (2015)CrossRefGoogle Scholar
  85. 85.
    Grancharova, A., Grøtli, E.I., Johansen, T.A.: Rotary-wing uavs path planning by distributed linear MPC with reconfigurable communication network topologies. In: IFAC Workshop on Distributed Estimation and Control in Networked Systems. Koblenz (2013)Google Scholar
  86. 86.
    Ho, D.T., Grøtli, E.I., Sujit, P.B., Johansen, T.A., Sousa, J.: Optimization of wireless sensor network and UAV, data acquisition. J. Intell. Robot. Syst. 78, 159–179 (2015)CrossRefGoogle Scholar
  87. 87.
    McGillivary, P., de Sousa, J.B., Martins, R., Rajan, K., Leroy, F.: Integrating autonomous underwater vessels, surface vessels and aircraft as persistent surveillance components of ocean observing studies. In: 2012 IEEE/OES Autonomous Underwater Vehicles (AUV), pp. 1–5 (2012)Google Scholar
  88. 88.
    Frew, E.W., Brown, T.X., Dixon, C., Henkel, D.: Establishment and maintenance of a delay tolerant network through decentralized mobility control. In: Proc. of the IEEE International Conference on Networking, Sensing and Control, pp. 584–589 (2006)Google Scholar
  89. 89.
    Grøtli, E.I., Johansen, T.A.: Motion- and communication-planning of unmanned aerial vehicles in delay tolerant network using mixed-integer. Linear Program. Model. Identif. Control 37(2), 77–97 (2016)CrossRefGoogle Scholar
  90. 90.
    Razif, M.A.M., Mokji, M., Zabidi, M.M.A.: Low complexity maritime surveillance video using background subtraction on h.264. In: 2015 International Symposium on Technology Management and Emerging Technologies (ISTMET), pp. 364–368 (2015)Google Scholar
  91. 91.
    Leira, F., Johansen, T.A., Fossen, T.I.: Automatic detection, classification and tracking of objects in the ocean surface from uavs using a thermal camera. In: IEEE Aerospace Conference, Big Sky (2015)Google Scholar
  92. 92.
    Curtin, T.B., Bellingham, J.G., Catipovic, J., Webb, D.: Autonomous oceanographic sampling networks. Oceanography 6, 86–94 (1993)CrossRefGoogle Scholar
  93. 93.
    Leonard, N.E., Paley, D.A., Davis, R.E., Fratantoni, D.M., Lekien, F., Zhang, F.: Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in monterey bay. J. Field Robot. 27, 718–740 (2010)CrossRefGoogle Scholar
  94. 94.
    Loy, M., Karingattil, R., Williams, L.: Ism-band and short range device regulatory compliance overview. http://www.ti.com/lit/an/swra048/swra048.pdf (2005), [Online; Accessed 13 July 2016]
  95. 95.
    Torrieri, D.: Principles of Spread-Spectrum Communication Systems, 2nd edn. Springer (2011)Google Scholar
  96. 96.
    Bekkadal, F.: Future maritime communications technologies. In: OCEANS 2009 - EUROPE, pp. 1–6 (2009)Google Scholar
  97. 97.
    Ge, Y., Kong, P.Y., Tham, C.K., Pathmasuntharam, J.S.: Connectivity and route analysis for a maritime communication network. In: 2007 6th International Conference on Information, Communications Signal Processing, pp. 1–5 (2007)Google Scholar
  98. 98.
    Friderikos, V., Papadaki, K., Dohler, M., Gkelias, A., Agvhami, H.: Linked waters. Commun. Eng. 3(2), 24–27 (2005)CrossRefGoogle Scholar
  99. 99.
    Kim, Y., Kim, J., Wang, Y., Chang, K., Park, J.W., Lim, Y.: Application scenarios of nautical ad-hoc network for maritime communications. In: OCEANS 2009, pp. 1–4 (2009)Google Scholar
  100. 100.
    Sozer, E.M., Stojanovic, M., Proakis, J.G.: Underwater acoustic networks. IEEE J. Ocean. Eng. 25 (1), 72–83 (2000)CrossRefGoogle Scholar
  101. 101.
    Kaushal, H., Kaddoum, G.: Underwater optical wireless communication. IEEE Access 4, 1518–1547 (2016)CrossRefGoogle Scholar
  102. 102.
    Mosca, F., Matte, G., Mignard, V., Rioblanc, M.: Low-frequency source for very long-range underwater communication. In: 2013 OCEANS - San Diego, pp. 1–5 (2013)Google Scholar
  103. 103.
    Stojanovic, M.: Low complexity ofdm detector for underwater acoustic channels. In: OCEANS 2006, pp. 1–6 (2006)Google Scholar
  104. 104.
    Chitre, M., Shahabudeen, S., Freitag, L., Stojanovic, M.: Recent advances in underwater acoustic communications & networking. In: OCEANS 2008. vol. 2008-Supplement, pp. 1–10 (2008)Google Scholar
  105. 105.
    Stojanovic, M., Catipovic, J., Proakis, J.G.: Adaptive multichannel combining and equalization for underwater acoustic communications. J. Acous. Soc. Amer. 94(3), 1621–1631 (1993).  https://doi.org/10.1121/1.408135 CrossRefGoogle Scholar
  106. 106.
    Murphy, C., Walls, J.M., Schneider, T., Eustice, R.M., Stojanovic, M., Singh, H.: Capture: A communications architecture for progressive transmission via underwater relays with eavesdropping. IEEE J. Ocean. Eng. 39(1), 120–130 (2014)CrossRefGoogle Scholar
  107. 107.
    Wang, Y., Liu, Y., Guo, Z.: Three-dimensional ocean sensor networks: A survey. J. Ocean Univ. China 11(4), 436–450 (2012)CrossRefGoogle Scholar
  108. 108.
    Pinto, J., Calado, P., Braga, J., Dias, P., Martins, R., Marques, E., Sousa, J.B.: Implementation of a control architecture for networked vehicle systems. In: IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles (NGCUV) (2012)Google Scholar
  109. 109.
    Mohsin, R.J., Woods, J., Shawkat, M.Q.: Density and mobility impact on manet routing protocols in a maritime environment. In: Science and Information Conference (SAI), 2015, pp. 1046–1051 (2015)Google Scholar
  110. 110.
    Xu, G., Shen, W., Wang, X.: Marine environment monitoring using wireless sensor networks: A systematic review. In: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 13–18 (2014)Google Scholar
  111. 111.
    Wehs, T., Janssen, M., Koch, C., von Cölln, G.: System architecture for data communication and localization under harsh environmental conditions in maritime automation. In: IEEE 10th International Conference on Industrial Informatics, pp. 1252–1257 (2012)Google Scholar
  112. 112.
    Sanctis, M.D., Cianca, E., Araniti, G., Bisio, I., Prasad, R.: Satellite communications supporting internet of remote things. IEEE Int. Things J. 3(1), 113–123 (2016)CrossRefGoogle Scholar
  113. 113.
    Martins, R.: Disruption/delay tolerant networking with low-bandwidth underwater acoustic modems. In: 2010 IEEE/OES Autonomous Underwater Vehicles (2010)Google Scholar
  114. 114.
    Lin, H.M., Ge, Y., Pang, A.C., Pathmasuntharam, J.: Performance study on delay tolerant networks in martitime communication environments. In: IEEE OCEANS (2010)Google Scholar
  115. 115.
    P, S.S., Kumar, S.S.: Sea water quality monitoring using smart sensor network. In: 2015 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 804–812 (2015)Google Scholar
  116. 116.
    Lambrinos, L., Djouvas, C., Chrysostomou, C.: Applying delay tolerant networking routing algorithms in maritime communications. In: 2013 IEEE 14th International Symposium and Workshops on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) (2013)Google Scholar
  117. 117.
    of Technology, M.I.: Moos-ivp home page (2017), http://oceanai.mit.edu/moos-ivp/pmwiki/pmwiki.php
  118. 118.
    Deering, D.S.E.: Internet Protocol, Version 6 (IPv6) Specification. RFC 2460 (2013) https://rfc-editor.org/rfc/rfc2460.txt
  119. 119.
    Luo, H., Wu, K., Guo, Z., Gu, L., Ni, L.M.: Ship detection with wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 23(7), 1336–1343 (2012)CrossRefGoogle Scholar
  120. 120.
    Ho, D.T., Grøtli, E.I., Sujit, P.B., Johansen, T.A., Sousa, J.B.: Optimization of wireless sensor network and uav data acquisition. J. Intell. Robot. Syst. 78(1), 159–179 (2015).  https://doi.org/10.1007/s10846-015-0175-5 CrossRefGoogle Scholar
  121. 121.
    Palattella, M.R., Accettura, N., Vilajosana, X., Watteyne, T., Grieco, L.A., Boggia, G., Dohler, M.: Standardized protocol stack for the internet of (important) things. IEEE Commun. Surv. Tutor. 15 (3), 1389–1406 (2013)CrossRefGoogle Scholar
  122. 122.
    Palma, D., Curado, M.: Resource Management in Mobile Computing Environments, chap. Scalable Routing Mechanisms for Mobile Ad Hoc Networks, pp. 65–114. Springer International Publishing, Cham (2014)Google Scholar
  123. 123.
    Kim, Y., Kim, J., Wang, Y., Chang, K., Park, J.W., Lim, Y.: Application scenarios of nautical ad-hoc network for maritime communications. In: OCEANS 2009 (2009)Google Scholar
  124. 124.
    Narten, D.T., Jinmei, T., Thomson, D.S.: IPv6 Stateless Address Autoconfiguration. RFC 4862 (2015) https://rfc-editor.org/rfc/rfc4862.txt
  125. 125.
    Kidston, D., Kunz, T.: Challenges and opportunities in managing maritime networks. IEEE Commun. Mag. 46(10), 162–168 (2008)CrossRefGoogle Scholar
  126. 126.
    Costanzo, S., Galluccio, L., Morabito, G., Palazzo, S.: Software Defined Wireless Networks: Unbridling SDNs. In: 2012 European Workshop on Software Defined Networking (EWSDN), pp. 1–6 (2012)Google Scholar
  127. 127.
    Galluccio, L., Milardo, S., Morabito, G., Palazzo, S.: Sdn-wise: Design, prototyping and experimentation of a stateful sdn solution for wireless sensor networks. In: 2015 IEEE Conference on Computer Communications (INFOCOM), pp. 513–521 (2015)Google Scholar

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Center for Autonomous Marine Operations and Systems (NTNU-AMOS), Department of Engineering CyberneticsNorwegian University of Science and Technology, Trondheim, NTNUTrondheimNorway
  2. 2.Department of Information Security and Communication TechnologyNTNUTrondheimNorway
  3. 3.Department of Electronic SystemsNTNUTrondheimNorway
  4. 4.SINTEF OceanTrondheimNorway
  5. 5.Department of Electrical and Computer EngineeringPorto UniversityPortoPortugal
  6. 6.School of Electrical EngineeringKTH Royal Institute of TechnologyStockholmSweden

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