Sensor-based motion control of autonomous underwater vehicles, part I: Modeling and low-complexity state estimation

George C. Karras; Charalampos P. Bechlioulis; Panos Marantos; Shahab Heshmati-alamdari; Kostas J. Kyriakopoulos

doi:10.1049/sbra525e_ch2

Sensor-based motion control of autonomous underwater vehicles, part I: Modeling and low-complexity state estimation

George C. Karras, Charalampos P. Bechlioulis, Panos Marantos, Shahab Heshmati-alamdari, Kostas J. Kyriakopoulos

Electrical Engineering

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

Abstract

The goal of this chapter is to provide the reader with the appropriate analytical methods, in order to derive a simple yet accurate vehicle model, design a state estimation algorithm that could be easily integrated into the embedded system framework of an underwater robotic vehicle and perform a fast online dynamic parameter identification.

Original language	English (US)
Title of host publication	Autonomous Underwater Vehicles
Publisher	Institution of Engineering and Technology
Pages	15-43
Number of pages	29
ISBN (Electronic)	9781785617034
DOIs	https://doi.org/10.1049/sbra525e_ch2
State	Published - Jan 1 2020

Keywords

Autonomous underwater vehicles
Autonomous underwater vehicles
Embedded system
Fast online dynamic parameter identification
Low-complexity state estimation
Marine system control
Mobile robots
Mobile robots
Sensor-based motion control
Simulation, modelling and identification
State estimation
State estimation
Telerobotics
Underwater robotic vehicle
Vehicle model

ASJC Scopus subject areas

General Engineering

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10.1049/sbra525e_ch2

Cite this

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title = "Sensor-based motion control of autonomous underwater vehicles, part I: Modeling and low-complexity state estimation",

abstract = "The goal of this chapter is to provide the reader with the appropriate analytical methods, in order to derive a simple yet accurate vehicle model, design a state estimation algorithm that could be easily integrated into the embedded system framework of an underwater robotic vehicle and perform a fast online dynamic parameter identification.",

keywords = "Autonomous underwater vehicles, Autonomous underwater vehicles, Embedded system, Fast online dynamic parameter identification, Low-complexity state estimation, Marine system control, Mobile robots, Mobile robots, Sensor-based motion control, Simulation, modelling and identification, State estimation, State estimation, Telerobotics, Underwater robotic vehicle, Vehicle model",

author = "Karras, {George C.} and Bechlioulis, {Charalampos P.} and Panos Marantos and Shahab Heshmati-alamdari and Kyriakopoulos, {Kostas J.}",

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doi = "10.1049/sbra525e_ch2",

language = "English (US)",

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AU - Bechlioulis, Charalampos P.

AU - Marantos, Panos

AU - Heshmati-alamdari, Shahab

AU - Kyriakopoulos, Kostas J.

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PY - 2020/1/1

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N2 - The goal of this chapter is to provide the reader with the appropriate analytical methods, in order to derive a simple yet accurate vehicle model, design a state estimation algorithm that could be easily integrated into the embedded system framework of an underwater robotic vehicle and perform a fast online dynamic parameter identification.

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KW - Embedded system

KW - Fast online dynamic parameter identification

KW - Low-complexity state estimation

KW - Marine system control

KW - Mobile robots

KW - Sensor-based motion control

KW - Simulation, modelling and identification

KW - State estimation

KW - Telerobotics

KW - Underwater robotic vehicle

KW - Vehicle model

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PB - Institution of Engineering and Technology

ER -

Sensor-based motion control of autonomous underwater vehicles, part I: Modeling and low-complexity state estimation

Abstract

Keywords

ASJC Scopus subject areas

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