Coordinated fleet of Autonomous Underwater Gliders (AUGs) can provide significant benefit to a number of marine applications including ocean sampling, mapping, surveillance and communication. Traditional techniques for navigating underwater vehicles have been designed for single-vehicle operations and do not scale well to multi-vehicle operations and missions. In this paper a navigation system for a fleet of AUGs is developed based on Networked DecentralizedModel Predictive Control (ND-MPC). The proposed approach coordinates a group of point-mass mobile agents to achieve a desired formation, while avoiding collisions between themselves. In order to obtain collision free paths, the approach integrates the required collision avoidance constraints. The fleet localization is performed by sensor fusion using adaptive extended Kalman filtering. The free collision and convergence properties are verified through simulations results. The proposed approach can be generalized to formation of heterogeneous autonomous agents.

Cooperative and decentralized navigation of autonomous underwater gliders using predictive control / A., Fonti; Freddi, Alessandro; Longhi, Sauro; Monteriu', Andrea. - XVIII(1):(2011), pp. 12813-12818. (Intervento presentato al convegno 18th IFAC World Congress (IFAC WC) tenutosi a Milan, Italy nel August 28 - September 2, 2011) [10.3182/20110828-6-IT-1002.02980].

Cooperative and decentralized navigation of autonomous underwater gliders using predictive control

FREDDI, ALESSANDRO;LONGHI, SAURO;MONTERIU', Andrea
2011-01-01

Abstract

Coordinated fleet of Autonomous Underwater Gliders (AUGs) can provide significant benefit to a number of marine applications including ocean sampling, mapping, surveillance and communication. Traditional techniques for navigating underwater vehicles have been designed for single-vehicle operations and do not scale well to multi-vehicle operations and missions. In this paper a navigation system for a fleet of AUGs is developed based on Networked DecentralizedModel Predictive Control (ND-MPC). The proposed approach coordinates a group of point-mass mobile agents to achieve a desired formation, while avoiding collisions between themselves. In order to obtain collision free paths, the approach integrates the required collision avoidance constraints. The fleet localization is performed by sensor fusion using adaptive extended Kalman filtering. The free collision and convergence properties are verified through simulations results. The proposed approach can be generalized to formation of heterogeneous autonomous agents.
2011
9783902661937
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/64485
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