Abstract
In this research, a framework for building Autonomous Underwater Vehicle (AUV) control algorithms that is based on the MOOS-IvP middleware is presented. The Sidescan Sonar Sensor (SSS) is commonly used to generate sonar images in which mine-like objects can be identified. A common mission specification would be to cover an entire area of seabed up to a specified confidence with the SSS. Here, a base station community is implemented that maintains a map of coverage confidence of the SSS, and provides the user with 2D and 3D simulations and the ability to implement advanced control schemes to achieve this mission. The development happens in two stages: 1) A minimalist configuration where only the necessary applications are used to develop and test outer loop control, and 2) A configuration that includes simulated hardware. The benefits are ease of use, faster development, and reduced hardware testing and cost.
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References
Eickstedt, D., Benjamin, M., Curcio, J.: Behavior based adaptive control for autonomous oceanographic sampling. In: IEEE International Conference on Robotics and Automation, pp. 4245–4250 (2007)
Jiang, D., Pang, Y., Qin, Z.: Coordination of multiple auvs based on moos-ivp. In: 8th IEEE International Conference on Control and Automation (ICCA), pp. 370–375 (2010)
Li, H., Popa, A., Thibault, C., Trentini, M., Seto, M.: A software framework for multi-agent control of multiple autonomous underwater vehicles for underwater mine counter-measures. In: 2010 International Conference on Autonomous and Intelligent Systems (AIS), pp. 1–6 (2010)
Benjamin, M., Newman, P., Schmidt, H., Leonard, J.: An overview of moos-ivp and a brief users guide to the ivp helm autonomy software. In:, http://dspace.mit.edu/bitstream/handle/1721.1/45569/MIT-CSAIL-TR-2009-028.pdf (June 2009)
Myers, V., Pinto, M.: Bounding the performance of sidescan sonar automatic target recognition algorithms using information theory. IET Radar Sonar Navig. 1(4), 266–273 (2007)
Navy, U.: The navy unmanned undersea vehicle (uuv) master plan (tech rep. a847115). Tech. rep., U.S. Navy (2004)
Newman, P.: Bridging communities with pmoosbridge, http://www.robots.ox.ac.uk/~pnewman/MOOSDocumentation/Essentials/Bridging/latex/MOOSBridge.pdf (June 2009)
Newman, P.: Moos meets matlab - imatlab, http://www.robots.ox.ac.uk/~pnewman/MOOSDocumeatation/tools/iMatlab/latex/iMatlab.pdf (March 17, 2009)
Newman, P.: Using the marine multivehicle simulator: umvs, (March 2009), http://www.robots.ox.ac.uk/~pnewman/MOOSDocumentation/tools/Simulation/Marine/latex/MarineMultiVehicleSimulator.pdf
Paull, L., Saeedi, S., Li, H., Myers, V.: An information gain based adaptive path planning method for an autonomous underwater vehicle using sidescan sonar. In: IEEE Conference on Automation Science and Engineering (CASE), pp. 835–840 (2010)
Sariel, S., Balch, T., Erdogan, N.: Naval mine countermeasure missions. IEEE Robotics Automation Magazine 15(1), 45–52 (2008)
Sotzing, C.C., Lane, D.M.: Improving the coordination efficiency of limited-communication multi-autonomus underwater vehicle operations using a multiagent architecture. Journal of Field Robotics 4, 412–429 (2010)
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Paull, L., Saeedi G., S., Seto, M., Li, H. (2011). A Multi-agent Framework with MOOS-IvP for Autonomous Underwater Vehicles with Sidescan Sonar Sensors. In: Kamel, M., Karray, F., Gueaieb, W., Khamis, A. (eds) Autonomous and Intelligent Systems. AIS 2011. Lecture Notes in Computer Science(), vol 6752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21538-4_5
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DOI: https://doi.org/10.1007/978-3-642-21538-4_5
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