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A Distributed Multi-level PSO Control Algorithm for Autonomous Underwater Vehicles

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Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2012)

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Abstract

This paper presents a distributed control technique based on the Particle Swarm Optimization algorithm and able to drive in unknown environments a group of autonomous robots to a common target point. In this paper, we consider in particular the case of underwater vehicles. The algorithm is able to deal with complex scenarios, frequently found in benthic exploration as e.g. in presence of obstacles, caves and tunnels, and to consider the case of a mobile target. Moreover, asynchronous data exchange and dynamic communication topologies are considered. Simulations results are provided to show the features of the proposed approach.

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Authors and Affiliations

  1. DEI, Department of Electrical, Electronic and Information Engineering, University of Bologna, Bologna, Italy

    Raffaele Grandi & Claudio Melchiorri

Authors
  1. Raffaele Grandi
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  2. Claudio Melchiorri
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Corresponding author

Correspondence to Raffaele Grandi .

Editor information

Editors and Affiliations

  1. Dalle Molle Institute for Artificial Intelligence (IDSIA), Manno-Lugano, Switzerland

    Gianni A. Di Caro

  2. CNRS UMR 5169, Research Center on Animal Cognition, Université Paul Sabatier, Toulouse, France

    Guy Theraulaz

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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Grandi, R., Melchiorri, C. (2014). A Distributed Multi-level PSO Control Algorithm for Autonomous Underwater Vehicles. In: Di Caro, G., Theraulaz, G. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 134. Springer, Cham. https://doi.org/10.1007/978-3-319-06944-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-06944-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06943-2

  • Online ISBN: 978-3-319-06944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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