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Plume Source Localization Based on Multi-AUV System

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Measuring Technology and Mechatronics Automation in Electrical Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 135))

Abstract

Multi-AUV system has advantages in high-accuracy localization with cooperative navigation and adaptive sampling with space–time distribution. It is expected to be a valuable platform in searching for hydrothermal vents, unexploded ordnances, and sources of hazardous chemicals or pollutants. This paper studies how to use multiple AUVs to locate these interesting sources, named the plume source localization problem. Two localization algorithms are proposed respectively based on time priority and distance priority. Simulation tests demonstrate that they are feasible and effective, and the distance priority based algorithm is better than the other with the higher localization accuracy and the shorter exploration time.

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References

  1. Marques L, Nunes U et al (2006) Particle swarm-based olfactory guided search [J]. Auton Robot 20(3):277–287

    Article  Google Scholar 

  2. Jatmiko W, Sekiyama K et al (2006) A mobile robots PSO-based for odor source localization in dynamic advection-diffusion environment. In: Proceedings of the 2006 IEEE/RSJ international conference on intelligent robots and systems

    Google Scholar 

  3. Jatmiko W, Mursanto P et al (2008) Modified PSO algorithm based on flow of wind for odor source localization problem in dynamic environments [J]. WSEAS Trans Syst 7(3):106–113

    Google Scholar 

  4. Bai S (2009) Research on active olfaction based on reinforcement learning algorithm. The master’s degree paper of Tianjin University

    Google Scholar 

  5. Zou Y, Luo D (2008) A modified ant colony algorithm used for multi-robot odor source localization. In: Proceedings of the 4th international conference on intelligent computing: advanced intelligent computing theories and applications-with aspects of artificial intelligent, pp 502–509

    Google Scholar 

  6. Marques L, Nunes U et al (2003) Odour searching with autonomous mobile robots: an evolutionary-based approach. In: Proceedings of IEEE international conference on advanced robotics, pp 494–500

    Google Scholar 

  7. Li W, Farrell JA et al (2001) Tracking of fluid-advected odor plumes: strategies inspired by insect orientation to pheromone [J]. Adapt Behav 9(3–4):143–169

    Article  Google Scholar 

  8. Kang X (2010) Research on chemical plume exploration via multiple AUVs with formation-keeping, The doctoral dissertation, Shenyang Institute of Automation CAS

    Google Scholar 

  9. Yu T, Zhang A (2010) Simulation environment and guidance system for AUV tracing chemical plume in 3-dimensions. In: The 2nd international Asia conference on informatics in control, automation and robotics, pp 407–411

    Google Scholar 

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Acknowledgments

Our works are supported by the Chinese National 863 Plan Program under grant 2007AA09Z207 and National Natural Science Foundation under grant 60805050.

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Correspondence to Hongli Xu .

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Xu, H., Kang, X. (2012). Plume Source Localization Based on Multi-AUV System. In: Hou, Z. (eds) Measuring Technology and Mechatronics Automation in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 135. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2185-6_46

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  • DOI: https://doi.org/10.1007/978-1-4614-2185-6_46

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-2184-9

  • Online ISBN: 978-1-4614-2185-6

  • eBook Packages: EngineeringEngineering (R0)

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