Robust Terrain-Aided Navigation through Sensor Fusion

Mårten Lager; Elin Anna Topp; Jacek Malec

doi:10.23919/FUSION45008.2020.9190578

Robust Terrain-Aided Navigation through Sensor Fusion

Mårten Lager, Elin Anna Topp, Jacek Malec

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

309 Nedladdningar (Pure)

Sammanfattning

To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships.

Originalspråk	engelska
Titel på värdpublikation	23rd International Conference on Information Fusion Virtual Conference
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Antal sidor	8
ISBN (elektroniskt)	978-0-578-64709-8
DOI	https://doi.org/10.23919/FUSION45008.2020.9190578
Status	Published - 2020 juli 6

Ämnesklassifikation (UKÄ)

Datorsystem

Tillgång till dokument

10.23919/FUSION45008.2020.9190578

Fusion2020 - Robust Terrain-Aided Navigation through Sensor Fusion - FinalPublicerad version, 16,5 MBLicens: Ospecificerad

1 Doktorsavhandling (sammanläggning)

Digital Cognitive Companions for Marine Vessels: On the Path Towards Autonomous Ships
Lager, M., 2021 jan. 19, Computer Science, Lund University. 249 s.
Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

Öppen tillgång
Fil

1 Avslutade
1 Aktiva

RobotLab LTH
Bagge Carlson, F. (Forskare), Johansson, R. (Forskare), Karlsson, M. (Forskare), Olofsson, B. (Forskare), Robertsson, A. (Forskare), Robertz, S. (Forskare), Haage, M. (Forskare), Malec, J. (Forskare), Nilsson, K. (Forskare), Nugues, P. (Forskare), Stenmark, M. (Forskare), Topp, E. A. (Forskare), Krueger, V. (Forskare), Åström, H. (Forskare), Mayr, M. (Forskare), Salt Ducaju, J. (Forskare), Nishimura, M. (Administratör), Wisbrant, J. (Projektkommunikatör), Dürr, A. (Forskare), Mayr, M. (Forskare), Nugues, P. (Forskare), Klang, M. (Forskningsingenjör), Klöckner, M. (Forskare), Nardi, L. (Forskare), Ahmad, F. (Forskare), Oxenstierna, J. (Forskare), Rizwan, M. (Forskare), Reichenbach, C. (Forskare), Bergström, J. (Forskare), Dell'Unto, N. (Forskare), Maunsbach, L. (Forskare), Åström, K. (Forskare), Blomdell, A. (Forskningsingenjör), Magnusson, M. (Forskare), Fransson, P.-A. (Forskare), Karayiannidis, Y. (Forskare), Johansson, A. T. (Forskare), Jia, Z. (Forskare), Laban, L. (Forskare), Wingqvist, B. (Forskare), Guberina, M. (Forskare), Jena, A. (Forskare), Westin, E. (Administratör), Frick, C. (Administratör), Pisarevskiy, A. (Forskningsingenjör), Nilsson, A. (Forskningsingenjör), Reitmann, S. (Forskare), Hvarfner, C. (Forskare), Stoltenberg, P. (Forskare) & Fregnan, S. (Forskare)
1993/01/01 → …
Projekt: Forskning
Digital Cognitive Companion for Marine Vessels
Lager, M. (PI), Malec, J. (Handledare) & Topp, E. A. (Handledare)
2016/01/01 → 2020/10/01
Projekt: Avhandling

RobotLab LTH Infrastruktur
Krueger, V. (Manager), Olofsson, B. (Manager), Karayiannidis, Y. (Manager), Haage, M. (Manager), Malec, J. (Manager) & Topp, E. A. (Manager)
Lunds Tekniska Högskola
Infrastruktur

1 Medlemskap i extern forskningsorganisation

WASP Affiliated Faculty
Topp, E. A. (medlem)
2021 feb. → …
Aktivitet: Konsultverksamhet, expertuppdrag och medlemskap › Medlemskap i extern forskningsorganisation

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@inproceedings{c79ba006156b43b8b12490eede92a874,

title = "Robust Terrain-Aided Navigation through Sensor Fusion",

abstract = "To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships. ",

keywords = "Unmanned Surface Vessel, Terrain Navigation, Particle Filter, Localization, Autonomous System",

author = "M{\aa}rten Lager and Topp, {Elin Anna} and Jacek Malec",

year = "2020",

month = jul,

day = "6",

doi = "10.23919/FUSION45008.2020.9190578",

language = "English",

booktitle = "23rd International Conference on Information Fusion Virtual Conference",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

TY - GEN

T1 - Robust Terrain-Aided Navigation through Sensor Fusion

AU - Lager, Mårten

AU - Topp, Elin Anna

AU - Malec, Jacek

PY - 2020/7/6

Y1 - 2020/7/6

N2 - To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships.

AB - To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships.

KW - Unmanned Surface Vessel

KW - Terrain Navigation

KW - Particle Filter

KW - Localization

KW - Autonomous System

U2 - 10.23919/FUSION45008.2020.9190578

DO - 10.23919/FUSION45008.2020.9190578

M3 - Paper in conference proceeding

BT - 23rd International Conference on Information Fusion Virtual Conference

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

ER -

Robust Terrain-Aided Navigation through Sensor Fusion

Sammanfattning

Ämnesklassifikation (UKÄ)

Tillgång till dokument

Fingeravtryck

Forskningsoutput

Digital Cognitive Companions for Marine Vessels: On the Path Towards Autonomous Ships

Projekt

RobotLab LTH

Digital Cognitive Companion for Marine Vessels

Utrustning

RobotLab LTH Infrastruktur

Aktiviteter

WASP Affiliated Faculty

Citera det här