Sonar-based AUV localization using an improved particle filter approach

Francesco Maurelli; Yvan Petillot; Angelos Mallios; Pere Ridao; Szymon Krupiński

doi:10.1109/OCEANSE.2009.5278196

Sonar-based AUV localization using an improved particle filter approach

Francesco Maurelli, Yvan Petillot, Angelos Mallios, Pere Ridao, Szymon Krupiński

School of Engineering & Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

This paper presents a sonar-based localization approach for an autonomous underwater vehicle, valid both in structured and unstructured environments. The presented system is based on a particle filter approach to represent the vehicle state. It uses a mechanical scanning imaging sonar, as the main sensor to have information about the environment. In this paper we present the chosen approach, highlighting the achieved results. An important feature is the robustness in presence of a partially unknown map, with excellent results for the test configuration. A particular attention is given to the exploration of the state space and to the reduction of computational complexity, leading to real-time capability. ©2009 IEEE.

Original language	English
Title of host publication	OCEANS '09 IEEE Bremen: Balancing Technology with Future Needs
Publisher	IEEE
DOIs	https://doi.org/10.1109/OCEANSE.2009.5278196
Publication status	Published - 11 May 2009
Event	OCEANS 2009 - Bremen, Germany Duration: 11 May 2009 → 14 May 2009

Conference

Conference	OCEANS 2009
Country/Territory	Germany
City	Bremen
Period	11/05/09 → 14/05/09
Other	Balancing technology with future needs

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10.1109/OCEANSE.2009.5278196

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title = "Sonar-based AUV localization using an improved particle filter approach",

abstract = "This paper presents a sonar-based localization approach for an autonomous underwater vehicle, valid both in structured and unstructured environments. The presented system is based on a particle filter approach to represent the vehicle state. It uses a mechanical scanning imaging sonar, as the main sensor to have information about the environment. In this paper we present the chosen approach, highlighting the achieved results. An important feature is the robustness in presence of a partially unknown map, with excellent results for the test configuration. A particular attention is given to the exploration of the state space and to the reduction of computational complexity, leading to real-time capability. {\textcopyright}2009 IEEE.",

author = "Francesco Maurelli and Yvan Petillot and Angelos Mallios and Pere Ridao and Szymon Krupi{\'n}ski",

year = "2009",

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doi = "10.1109/OCEANSE.2009.5278196",

language = "English",

booktitle = "OCEANS '09 IEEE Bremen: Balancing Technology with Future Needs",

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note = "OCEANS 2009 ; Conference date: 11-05-2009 Through 14-05-2009",

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T1 - Sonar-based AUV localization using an improved particle filter approach

AU - Maurelli, Francesco

AU - Petillot, Yvan

AU - Mallios, Angelos

AU - Ridao, Pere

AU - Krupiński, Szymon

PY - 2009/5/11

Y1 - 2009/5/11

N2 - This paper presents a sonar-based localization approach for an autonomous underwater vehicle, valid both in structured and unstructured environments. The presented system is based on a particle filter approach to represent the vehicle state. It uses a mechanical scanning imaging sonar, as the main sensor to have information about the environment. In this paper we present the chosen approach, highlighting the achieved results. An important feature is the robustness in presence of a partially unknown map, with excellent results for the test configuration. A particular attention is given to the exploration of the state space and to the reduction of computational complexity, leading to real-time capability. ©2009 IEEE.

AB - This paper presents a sonar-based localization approach for an autonomous underwater vehicle, valid both in structured and unstructured environments. The presented system is based on a particle filter approach to represent the vehicle state. It uses a mechanical scanning imaging sonar, as the main sensor to have information about the environment. In this paper we present the chosen approach, highlighting the achieved results. An important feature is the robustness in presence of a partially unknown map, with excellent results for the test configuration. A particular attention is given to the exploration of the state space and to the reduction of computational complexity, leading to real-time capability. ©2009 IEEE.

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DO - 10.1109/OCEANSE.2009.5278196

M3 - Conference contribution

BT - OCEANS '09 IEEE Bremen: Balancing Technology with Future Needs

PB - IEEE

T2 - OCEANS 2009

Y2 - 11 May 2009 through 14 May 2009

ER -

Sonar-based AUV localization using an improved particle filter approach

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