A particle filter approach for AUV localization

Francesco Maurelli; Szymon Krupińskiy; Yvan Petillot; Joaquim Salviz

doi:10.1109/OCEANS.2008.5152014

A particle filter approach for AUV localization

Francesco Maurelli, Szymon Krupińskiy, Yvan Petillot, Joaquim Salviz

School of Engineering & Physical Sciences

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

35 Citations (Scopus)

Abstract

This paper presents a sonar-based localization approach for an autonomous underwater vehicle, in structured and unstructured environments. The system is based on a particle filter approach to represent the vehicle state and it uses a mechanically scanned profiling sonar, acquiring range profiles. A modification to the standard particle filter algorithm is proposed, in order to explore the state space in a more effective way and to reduce computational complexity. The proposed system was validated both in simulation and in trials involving a real vehicle, showing a high robustness and real-time capabilities. © 2008 IEEE.

Original language	English
Title of host publication	OCEANS 2008
DOIs	https://doi.org/10.1109/OCEANS.2008.5152014
Publication status	Published - 2008
Event	OCEANS 2008 - Quebec City, QC, Canada Duration: 15 Sept 2008 → 18 Sept 2008

Conference

Conference	OCEANS 2008
Country/Territory	Canada
City	Quebec City, QC
Period	15/09/08 → 18/09/08

Access to Document

10.1109/OCEANS.2008.5152014

Cite this

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title = "A particle filter approach for AUV localization",

abstract = "This paper presents a sonar-based localization approach for an autonomous underwater vehicle, in structured and unstructured environments. The system is based on a particle filter approach to represent the vehicle state and it uses a mechanically scanned profiling sonar, acquiring range profiles. A modification to the standard particle filter algorithm is proposed, in order to explore the state space in a more effective way and to reduce computational complexity. The proposed system was validated both in simulation and in trials involving a real vehicle, showing a high robustness and real-time capabilities. {\textcopyright} 2008 IEEE.",

author = "Francesco Maurelli and Szymon Krupi{\'n}skiy and Yvan Petillot and Joaquim Salviz",

year = "2008",

doi = "10.1109/OCEANS.2008.5152014",

language = "English",

isbn = "9781424426201",

booktitle = "OCEANS 2008",

note = "OCEANS 2008 ; Conference date: 15-09-2008 Through 18-09-2008",

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AU - Maurelli, Francesco

AU - Krupińskiy, Szymon

AU - Petillot, Yvan

AU - Salviz, Joaquim

PY - 2008

Y1 - 2008

N2 - This paper presents a sonar-based localization approach for an autonomous underwater vehicle, in structured and unstructured environments. The system is based on a particle filter approach to represent the vehicle state and it uses a mechanically scanned profiling sonar, acquiring range profiles. A modification to the standard particle filter algorithm is proposed, in order to explore the state space in a more effective way and to reduce computational complexity. The proposed system was validated both in simulation and in trials involving a real vehicle, showing a high robustness and real-time capabilities. © 2008 IEEE.

AB - This paper presents a sonar-based localization approach for an autonomous underwater vehicle, in structured and unstructured environments. The system is based on a particle filter approach to represent the vehicle state and it uses a mechanically scanned profiling sonar, acquiring range profiles. A modification to the standard particle filter algorithm is proposed, in order to explore the state space in a more effective way and to reduce computational complexity. The proposed system was validated both in simulation and in trials involving a real vehicle, showing a high robustness and real-time capabilities. © 2008 IEEE.

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U2 - 10.1109/OCEANS.2008.5152014

DO - 10.1109/OCEANS.2008.5152014

M3 - Conference contribution

SN - 9781424426201

BT - OCEANS 2008

T2 - OCEANS 2008

Y2 - 15 September 2008 through 18 September 2008

ER -

A particle filter approach for AUV localization

Abstract

Conference

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