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Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile, Italy
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3 Papers

Semi-centralized Reconstruction of Robot Swarm Topologies - The Largest Laplacian Eigenvalue and High Frequency Noise are used to Calculate the Adjacency Matrix of an Underwater Swarm from Time-series

Topics: Distributed Control Systems; Network Robotics; Space and Underwater Robotics

Authors: Vincenzo Fioriti , Stefano Chiesa and Fabio Fratichini

Affiliation: ENEA C. R. Casaccia, Italy

Digital Object Identifier: 10.5220/0004421800740081

Proceedings of ICINCO 2013, ISBN: 978-989-8565-70-9

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An important task in underwater autonomous vehicle swarm management is the knowledge of the graph topology, to be obtained with the minimum possible communication exchanges and amid heavy interferences and background noises. Despite the importance of the task, this problem is still partially unsolved. Recently, the Fast Fourier Transform and the addition of white noise to consensus signals have been proposed independently to determine respectively the laplacian spectrum and the adjacency matrix of the graph of interacting agents from consensus time series, but both methodologies suffer technical difficulties. In this paper, we combine them in order to simplify calculations, save energy and avoid topological reconstruction errors using only the largest eigenvalue of the spectrum and instead of white noise, a high frequency, low amplitude noise. Numerical simulations of several swarms (random, small-world, pipeline, grid) show an exact reconstruction of the configuration topologies.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Distributed Control Systems

Intelligent Control Systems and Optimization

Robotics and Automation

Informatics in Control, Automation and Robotics

Network Robotics

Space and Underwater Robotics

Three Dimensional Localisation in Underwater Swarms through a Kalman Approach

Topics: Distributed Control Systems; Space and Underwater Robotics; Mobile Robots and Autonomous Systems; Sensors Fusion

Authors: Fabio Fratichini 1 , Stefano Chiesa 2 and Sergio Taraglio 2

Affiliations: 1 ENEA and University of Roma Tre, Italy , 2 ENEA, Italy

Digital Object Identifier: 10.5220/0004457502150221

Proceedings of ICINCO 2013, ISBN: 978-989-8565-71-6

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A three dimensional localisation algorithm for a swarm of underwater vehicles is presented. The proposed approach is grounded on an extended Kalman filter (EKF) scheme used to fuse some proprioceptive data such as the vessel’s speed and some esteroceptive measurement such as the time of flight (TOF) sonar distance of the companion vessels. The results of several simulations are presented. Some considerations about the available underwater bandwidth and the communication needed by the approach are discussed.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Distributed Control Systems

Mobile Robots and Autonomous Systems

Signal Processing, Sensors, Systems Modeling and Control

Informatics in Control, Automation and Robotics

Robotics and Automation

Space and Underwater Robotics
Intelligent Control Systems and Optimization

Sensors Fusion

Flocking Approach to Spatial Configuration Control in Underwater Swarms

Topics: Distributed Control Systems; Autonomous Agents; Mobile Robots and Autonomous Systems; Engineering Applications

Authors: Stefano Chiesa 1 , Sergio Taraglio 2 , Stefano Pagnottelli 3 and Paolo Valigi 3

Affiliations: 1 University of Roma Tre and ENEA, Italy , 2 ENEA, Italy , 3 University of Perugia, Italy

Digital Object Identifier: 10.5220/0004036903130316

Proceedings of ICINCO 2012, ISBN: 978-989-8565-21-1

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A modification of the flocking algorithm approach for a swarm of underwater vehicles is introduced. The proposed approach relaxes the symmetry of the inter vehicle interaction. It is thus possible to change the swarm spatial configuration assuming different formations with varying parameters. The swarm geometry is changed with a very limited effort, exploiting the capability of the flocking approach to make emerge a large scale arrangement. Examples of proposed variations are provided. The vehicles are dynamically modelled and the relative non holonomic proportional derivative controller is described. Experimental data are gathered from many vehicle physical simulations and graphically presented.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Autonomous Agents

Informatics in Control, Automation and Robotics

Robotics and Automation

Distributed Control Systems

Intelligent Control Systems and Optimization

Signal Processing, Sensors, Systems Modeling and Control
Engineering Applications

Mobile Robots and Autonomous Systems

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