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Development and Experimental Tests of a ROS Multi-agent Structure for Autonomous Surface Vehicles

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Abstract

Robotic structures that couple autonomous surface vehicles and unmanned underwater vehicles in integrated systems with various levels of cooperation provide interesting solutions to the problem of developing efficient, versatile and cost effective tools for exploration, monitoring and exploitation of the underwater environment. In this paper we describe the development and preliminary field testing of an autonomous surface vehichle that can automatically track, deploy and recover a small remotely operated vehicle, which is guided from a shore-ground station. This goal is achieved by exploiting two-ways transmission of data and commands through the umbilical and a wireless link with a shore-ground station. In this way, pilots can experiment telepresence in the underwater environment, avoiding the need of expensive and logistically demanding manned supply vessel. The vehicle is a small aluminum hull boat, equipped with a steering outboard electric motor. A multi-agent system in the ROS framework is proposed for the robotic structure. The use of commercial-off-the-shelf components and the choice of a multi-agent ROS architecture are a mean to reduce costs and to assure performances, modularity and versatility. Field tests in both supervised and autonomous guidance mode have been performed in order to assess the basic functionalities of the system and their results are illustrated and discussed.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Ancona, Italy

    Giuseppe Conte, David Scaradozzi, Daniele Mannocchi, Paolo Raspa, Luca Panebianco & Laura Screpanti

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  1. Giuseppe Conte
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  2. David Scaradozzi
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  3. Daniele Mannocchi
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  4. Paolo Raspa
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  5. Luca Panebianco
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  6. Laura Screpanti
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Correspondence to Giuseppe Conte.

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Conte, G., Scaradozzi, D., Mannocchi, D. et al. Development and Experimental Tests of a ROS Multi-agent Structure for Autonomous Surface Vehicles. J Intell Robot Syst 92, 705–718 (2018). https://doi.org/10.1007/s10846-017-0700-9

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  • DOI: https://doi.org/10.1007/s10846-017-0700-9

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