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Underwater Localization and Environment Mapping Using Wireless Robots

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Abstract

Localization and mapping are the fundamental ability for underwater robots to carry out exploration and searching tasks autonomously. This paper presents a novel approach to localization and mapping of a school of wirelessly connected underwater robotic fish (URF). It is based on both Cooperative Localization Particle Filter (CLPF) scheme and Occupancy Grid Mapping Algorithm (OGMA). Using the probabilistic framework, the proposed CLPF has the major advantage that no prior knowledge about the kinematic model of URF is required to achieve accurate 3D localization. It works well when the number of mobile beacons is less than four, which is the minimum number for some traditional localization algorithms. The localization result of CLPF is fed into OGMA to build the environment map. The performance of the proposed algorithms is evaluated through extensive simulation experiments, and results verify the feasibility and effectiveness of the proposed strategy.

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References

  1. Akyildiz, I., Pompili, D., & Melodia, T. (2005). Underwater acoustic sensor networks: Research challenges. Ad Hoc Networks, 3(3), 257–279.

    Article  Google Scholar 

  2. Baggio, A., & Langendoen, K. (2008). Monte carlo localization for mobile wireless sensor networks. Ad Hoc Networks, 6(5), 718–733.

    Article  Google Scholar 

  3. Bahr, A., Leonard, J., & Fallon, M. (2009). Cooperative localization for autonomous underwater vehicles. The International Journal of Robotics Research, 28(6), 714–728.

    Article  Google Scholar 

  4. Bailey, T., & Durrant-Whyte, H. (2006). Simultaneous localization and mapping (slam): Part ii. IEEE Robotics & Automation Magazine, 13(3), 108–117.

    Article  Google Scholar 

  5. Dissanayake, M., Newman, P., Clark, S., Durrant-Whyte, H., & Csorba, M. (2001). A solution to the simultaneous localization and map building (slam) problem. IEEE Transactions on Robotics and Automation, 17(3), 229–241.

    Article  Google Scholar 

  6. Durrant-Whyte, H., & Bailey, T. (2006). Simultaneous localization and mapping: Part i. IEEE Robotics & Automation Magazine, 13(2), 99–110.

    Article  Google Scholar 

  7. Elfes, A. (1989). Occupancy grids: A probabilistic framework for robot perception and navigation. PhD thesis, Carnegie Mellon University.

  8. Erol-Kantarci, M., Mouftah, H., & Oktug, S. (2011). A survey of architectures and localization techniques for underwater acoustic sensor networks. Communications Surveys and Tutorials, 13(3), 487–502.

    Article  Google Scholar 

  9. Fallon, M., Papadopoulos, G., Leonard, J., & Patrikalakis, N. (2010). Cooperative auv navigation using a single maneuvering surface craft. The International Journal of Robotics Research, 29(12), 1461–1474.

    Article  Google Scholar 

  10. He, B., Liang, Y., Feng, X., Nian, R., Yan, T., Li, M., et al. (2012). Auv slam and experiments using a mechanical scanning forward-looking sonar. Sensors, 12(7), 9386–9410.

    Article  Google Scholar 

  11. Hong, X., Gerla, M., Pei, G., & Chiang, C. (1999). A group mobility model for ad hoc wireless networks. In Proceedings of the 2nd ACM international workshop on modeling, analysis and simulation of wireless and mobile systems (pp. 53–60), ACM.

  12. Huang, Y., Liang, W., Yu, H., & Xiao, Y. (2008). Target tracking based on a distributed particle filter in underwater sensor networks. Wireless Communications and Mobile Computing, 8(8), 1023–1033.

    Article  Google Scholar 

  13. Joordens, M., & Jamshidi, M. (2010). Consensus control for a system of underwater swarm robots. IEEE Systems Journal, 4(1), 65–73.

    Article  Google Scholar 

  14. Knoll, A., & Prasad, R. (2012). Wireless robotics: A highly promising case for standardization. Wireless Personal Communications, 64, 611–617.

    Article  Google Scholar 

  15. Kottege, N., & Zimmer, U. (2011). Underwater acoustic localization for small submersibles. Journal of Field Robotics, 28(1), 40–69.

    Article  Google Scholar 

  16. Kumar, S., & Lobiyal, D. (2012). An advanced dv-hop localization algorithm for wireless sensor networks. Wireless Personal Communications, 1–21. doi:10.1007/s11277-012-0880-3.

  17. Lee, P., Jeon, B., Kim, S., Choi, H., Lee, C., Aoki, T., & Hyakudome, T. (2004). An integrated navigation system for autonomous underwater vehicles with two range sonars, inertial sensors and doppler velocity log. In OCEANS’04. MTTS/IEEE TECHNO-OCEAN’04, IEEE (Vol. 3, pp. 1586–1593).

  18. Lee, S., & Kim, K. (2012). Localization with a mobile beacon in underwater acoustic sensor networks. Sensors, 12(5), 5486–5501.

    Article  Google Scholar 

  19. Lin, C. F., Chang, S. H., Lee, C. C., Wu, W. C., Chen, W. H., Chang, K. H., Lee, J., & Parinov, I. (2012). Underwater acoustic multimedia communication based on mimocofdm. Wireless Personal Communications (Online First).

  20. Poncela, J., Aguayo, M., & Otero, P. (2012). Wireless underwater communications. Wireless Personal Communications, 64, 547–560.

    Article  Google Scholar 

  21. Ribas, D., Ridao, P., Tardós, J., & Neira, J. (2008). Underwater slam in man-made structured environments. Journal of Field Robotics, 25(11–12), 898–921.

    Article  MATH  Google Scholar 

  22. Rubinstein, R., & Kroese, D. (2007). Simulation and the Monte Carlo method (Vol. 707). Wiley, New York.

  23. Tao, J., Zheng, Y., Xiao, C., & Yang, T. (2010). Robust mimo underwater acoustic communications using turbo block decision-feedback equalization. IEEE Journal of Oceanic Engineering, 35(4), 948–960.

    Article  Google Scholar 

  24. Thrun, S., Burgard, W., Fox, D., et al. (2005). Probabilistic robotics (Vol. 1). Cambridge, MA: MIT press.

    MATH  Google Scholar 

  25. Yoerger, D., Jakuba, M., Bradley, A., & Bingham, B. (2007). Techniques for deep sea near bottom survey using an autonomous underwater vehicle. The International Journal of Robotics Research, 26(1), 41–54.

    Article  Google Scholar 

  26. Yun, X., Bachmann, E., McGhee, R., Whalen, R., Roberts, R., Knapp, R., et al. (1999). Testing and evaluation of an integrated gps/ins system for small auv navigation. IEEE Journal Of Oceanic Engineering, 24(3), 396–404.

    Article  Google Scholar 

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Acknowledgments

This research has been financially supported by National Natural Science foundation of China (Grant number 61165016) and by the University of Essex (Grant of Building Partnerships for Knowledge Exchange). Sen Wang and Ling Chen have been financially supported by Essex University Scholarship and China Scholarship Council. Our thanks also go to Robin Dowling for his technical support during the experiments.

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Authors and Affiliations

  1. School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK

    Sen Wang, Ling Chen & Huosheng Hu

  2. College of Chemical Engineering, Qinghai University, Xining, China

    Zhibin Xue

  3. College of Information Science and Technology, Xiamen University, Xiamen, China

    Wei Pan

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  1. Sen Wang
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  2. Ling Chen
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  3. Huosheng Hu
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  4. Zhibin Xue
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  5. Wei Pan
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Correspondence to Huosheng Hu.

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Wang, S., Chen, L., Hu, H. et al. Underwater Localization and Environment Mapping Using Wireless Robots. Wireless Pers Commun 70, 1147–1170 (2013). https://doi.org/10.1007/s11277-013-1106-z

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