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On the Influence of Localisation and Communication Error on the Behaviour of a Swarm of Autonomous Underwater Vehicles

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Recent Advances in Soft Computing (MENDEL 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 837))

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Abstract

The long term goal of this research is to develop a swarm of autonomous underwater vehicles (AUVs), which can be used to locate submarine sources of interest, like dumped radioactive waste or ammunition. The overall search strategy of the swarm is based on particle swarm optimisation (PSO). Standard PSO relies on correct localisation and timely communication in order to be able to converge towards the global optimum. However, underwater communication is slow and unreliable and the exact localisation of an AUV is difficult. Therefore, this paper presents an empirical study of the effect of communication and localisation error on the convergence capabilities of PSO. A simulation based on cellular automata is presented and a model of communication and localisation error is incorporated into the PSO. It is shown that both types of errors have a negative effect on the performance of the search, with localisation error having the greater contribution.

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References

  1. Zielinski, O., Busch, J.A., Cembella, A.D., Daly, K.L., Engelbrektsson, J., Hannides, A.K., Schmidt, H.: Detecting marine hazardous substances and organisms: sensors for pollutants, toxins and pathogens. Ocean Sci. 5, 329–349 (2009)

    Article  Google Scholar 

  2. Zielinski, O.: Airborne pollution surveillance using multi-sensor systems – new sensors and algorithms for improved oil spill detection and polluter identification. Sea Technol. 44(10), 28–32 (2003)

    Google Scholar 

  3. Moore, W.S.: The effect of submarine groundwater discharge on the ocean. Ann. Rev. Mar. Sci. 2, 59–88 (2010)

    Article  Google Scholar 

  4. Nelson, C.E., Donahue, M.J., Dulaiova, H., Goldberg, S.J., La Valle, F.F., Lubarsky, K., Miyano, J., Richardson, C., Silbiger, N.J., Thomas, F.I.: Fluorescent dissolved organic matter as a multivariate biogeochemical tracer of submarine groundwater discharge in coral reef ecosystems. Mar. Chem. 177, 232–243 (2015)

    Article  Google Scholar 

  5. Beck, M., Reckhardt, A., Amelsberg, J., Bartholomä, A., Brumsack, H.J., Cypionka, H., Dittmar, T., Engelen, B., Greskowiak, J., Hillebrand, H., Holtappels, M., Neuholz, R., Köster, J., Kuypers, M.M.M., Massmann, G., Meier, D., Niggemann, J., Paffrath, R., Pahnke, K., Rovo, S., Striebel, M., Vandieken, V., Wehrmann, A., Zielinski, I.: The drivers of biogeochemistry in beach ecosystems: a crossshore transect from the dunes to the low water line. Mar. Chem. 190, 35–50 (2017)

    Article  Google Scholar 

  6. Evans, T.B., Wilson, A.M.: Groundwater transport and the freshwater–saltwater interface below sandy beaches. J. Hydrol. 538, 563–573 (2016)

    Article  Google Scholar 

  7. Nolle, L.: On a search strategy for collaborating autonomous underwater vehicles. In: Mendel 2015, 21st International Conference on Soft Computing, Brno, CZ, pp. 159–164 (2015)

    Google Scholar 

  8. Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm Intelligence. Academic Press, Cambridge (2001)

    Google Scholar 

  9. Bansal, J.C., Singh, P.K., Saraswat, M., Verma, A., Jadon, S.S., Abraham, A.: Inertia weight strategies in particle swarm optimization. In: Third World Congress on Nature and Biologically Inspired Computing, Salamanca, Spain, 19–21 October, pp. 633–640 (2011)

    Google Scholar 

  10. Wolfram, S.: Universality and complexity in cellular automata. Physica D 10(1–2), 1–35 (1984)

    Article  MathSciNet  Google Scholar 

  11. Moore, C., Barnard, A., Fietzek, P., Lewis, M.R., Sosik, H.M., White, S., Zielinski, O.: Optical tools for ocean monitoring and research. Ocean Sci. 5, 661–684 (2009)

    Article  Google Scholar 

  12. Zielinski, O., Voß, D., Saworski, B., Fiedler, B., Körtzinger, A.: Computation of nitrate concentrations in turbid coastal waters using an in situ ultraviolet spectrophotometer. J. Sea Res. 65, 456–460 (2011)

    Article  Google Scholar 

  13. Nolle, L., Thormählen, H., Musa, H.: Simulation of submarine groundwater discharge of dissolved organic matter using cellular automata. In: 30st European Conference on Modelling and Simulation ECMS 2016, pp. 265–269 (2016)

    Google Scholar 

  14. Tholen, C., Nolle, L., Zielinski, O.: On the effect of neighborhood schemes and cell shape on the behaviour of cellular automata applied to the simulation of submarine groundwater discharge. In: 31th European Conference on Modelling and Simulation ECMS 2017, pp. 255–261 (2017)

    Google Scholar 

  15. Jiménez, A., Posadas, A.M., Marfil, J.M.: A probabilistic seismic hazard model based on cellular automata and information theory. Nonlinear Processes Geophys. 12(3), 381–396 (2005)

    Article  Google Scholar 

  16. Lurton, X.: An introduction to underwater acoustics: principles and applications. New York Springer, London (2002)

    Google Scholar 

  17. Levinson, E., Ter Horst, J., Willcocks, M.: The next generation marine inertial navigator is here now. In: 1994 Position Location and Navigation Symposium, Las Vegas, NV, pp. 121–127. IEEE (1994)

    Google Scholar 

  18. Curey, R.K., Ash, M.E., Thielman, L.O., Barker, C.H.: Proposed IEEE inertial systems terminology standard and other inertial sensor standards. In: PLANS 2004. Position Location and Navigation Symposium, pp. 83–90 (2004)

    Google Scholar 

  19. Rigby, P., Pizarro, O., Williams, S.B.: Towards geo-referenced AUV navigation through fusion of USBL and DVL measurements. In: OCEANS 2006, Boston, MA, pp. 1–6 (2006)

    Google Scholar 

  20. Dunbabin, M., Roberts, J., Usher, K., Winstanley, G., Corke, P.: A hybrid AUV design for shallow water reef navigation. In: 2005 IEEE International Conference on Robotics and Automation, pp. 2105–2110 (2005)

    Google Scholar 

  21. Dunbabin, M., Corke, P., Vasilescu, I., Rus, D.: Data muling over underwater wireless sensor networks using an autonomous underwater vehicle. In: 2006 IEEE International Conference on Robotics and Automation, pp. 2091–2098 (2006)

    Google Scholar 

  22. Edwards, A.M., Phillips, R.A., Watkins, N.W., Freeman, M.P., Murphy, E.J., Afanasyev, V., Buldyrev, S.V., da Luz, M.G.E., Raposo, E.P., Stanley, H.E., Viswanathan, G.M.: Revisiting levy flight search patterns of wandering albatrosses, bumblebees and deer. Nature 449, 1044–1049 (2007)

    Article  Google Scholar 

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Correspondence to Christoph Tholen .

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Tholen, C., Nolle, L., Werner, J. (2019). On the Influence of Localisation and Communication Error on the Behaviour of a Swarm of Autonomous Underwater Vehicles. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_6

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