Developing reliable navigation strategies is mandatory in the field of Underwater Robotics and in particular for Autonomous Underwater Vehicles (AUVs) to ensure the correct achievement of a mission. Underwater navigation is still nowadays critical, e.g. due to lack of access to satellite navigation systems (e.g. the Global Positioning System, GPS): an AUV typically proceeds for long time intervals only relying on the measurements of its on-board sensors, without any communication with the outside environment. In this context, the filtering algorithm for the estimation of the AUV state is a key factor for the performance of the system; i.e. the filtering algorithm used to estimate the state of the AUV has to guarantee a satisfactory underwater navigation accuracy. In this paper, the authors present an underwater navigation system which exploits measurements from an Inertial Measurement Unit (IMU), Doppler Velocity Log (DVL) and a Pressure Sensor (PS) for the depth, and relies on either an Extended Kalman Filter (EKF) or an Unscented Kalman Filter (UKF) for state estimation. A comparison between the EKF approach, classically adopted in the field of underwater robotics and the UKF is given. These navigation algorithms have been experimentally validated through the data related to some sea tests with the Typhoon class AUVs, designed and assembled by the Department of Industrial Engineering of the Florence University (DIEF) for exploration and surveillance of underwater archaeological sites in the framework of the THESAURUS and European ARROWS projects. The comparison results are significant as the two filtering strategies are based on the same process and sensors models. At this initial stage of the research activity, the navigation algorithms have been tested offline. The presented results rely on the experimental navigation data acquired during two different sea missions: in the first one, Typhoon AUV #1 navigated in a Remotely Operated Vehicle (ROV) mode near Livorno, Italy, during the final demo of THESAURUS project (held in August 2013); in the latter Typhoon AUV #2 autonomously navigated near La Spezia in the framework of the NATO CommsNet13 experiment, Italy (held in September 2013). The achieved results demonstrate the effectiveness of both navigation algorithms and the superiority of the UKF without increasing the computational load. The algorithms are both affordable for online on-board AUV implementation and new tests at sea are planned for spring 2015.
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ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 2–5, 2015
Boston, Massachusetts, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-5712-0
PROCEEDINGS PAPER
An Innovative Navigation Strategy for Autonomous Underwater Vehicles: An Unscented Kalman Filter Based Approach
Benedetto Allotta,
Benedetto Allotta
University of Florence, Florence, Italy
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Riccardo Costanzi,
Riccardo Costanzi
University of Florence, Florence, Italy
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Enrico Meli,
Enrico Meli
University of Florence, Florence, Italy
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Alessandro Ridolfi,
Alessandro Ridolfi
University of Florence, Florence, Italy
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Luigi Chisci,
Luigi Chisci
University of Florence, Florence, Italy
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Claudio Fantacci,
Claudio Fantacci
University of Florence, Florence, Italy
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Andrea Caiti,
Andrea Caiti
University of Pisa, Pisa, Italy
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Francesco Di Corato,
Francesco Di Corato
University of Pisa, Pisa, Italy
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Davide Fenucci
Davide Fenucci
University of Pisa, Pisa, Italy
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Benedetto Allotta
University of Florence, Florence, Italy
Riccardo Costanzi
University of Florence, Florence, Italy
Enrico Meli
University of Florence, Florence, Italy
Alessandro Ridolfi
University of Florence, Florence, Italy
Luigi Chisci
University of Florence, Florence, Italy
Claudio Fantacci
University of Florence, Florence, Italy
Andrea Caiti
University of Pisa, Pisa, Italy
Francesco Di Corato
University of Pisa, Pisa, Italy
Davide Fenucci
University of Pisa, Pisa, Italy
Paper No:
DETC2015-46432, V05AT08A052; 10 pages
Published Online:
January 19, 2016
Citation
Allotta, B, Costanzi, R, Meli, E, Ridolfi, A, Chisci, L, Fantacci, C, Caiti, A, Di Corato, F, & Fenucci, D. "An Innovative Navigation Strategy for Autonomous Underwater Vehicles: An Unscented Kalman Filter Based Approach." Proceedings of the ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 5A: 39th Mechanisms and Robotics Conference. Boston, Massachusetts, USA. August 2–5, 2015. V05AT08A052. ASME. https://doi.org/10.1115/DETC2015-46432
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