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To smooth or to filter: a comparative study of state estimation approaches for vision-based autonomous underwater docking
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0002-8738-1576
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0003-2336-9401
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0001-8303-7826
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0003-3337-1900
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2024 (English)In: OCEANS 2024 - SINGAPORE, Institute of Electrical and Electronics Engineers (IEEE) , 2024Conference paper, Published paper (Refereed)
Abstract [en]

Terminal docking is an important step towards long-term underwater residency of Autonomous Underwater Vehicles (AUVs). An important part is to correctly estimate the relative position between the AUV and the docking station. While there are many solutions to this problem, it is unclear how they perform with respect to each other in terms of accuracy and computational performance. We propose a side by side comparison of a Rao-Blackwellized particle filter (RBPF) with a Maximum-A-Posteriori (MAP) method in a vision-based terminal homing scenario. Both methods are evaluated in a simulation study based on performance under different uncertainties. Subsequently, they are validated using real-world data from field tests. The comparison shows that in the simulation study, the smoothing performs more accurate than the RBPF, whereas on the experimental data, they perform equally. However, the smoothing requires less computational power compared to the RBPF.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024.
Keywords [en]
terminal docking, AUV, RBPF, factor graphs, vision-based
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:kth:diva-357069DOI: 10.1109/OCEANS51537.2024.10682396ISI: 001332919300269Scopus ID: 2-s2.0-85206495193OAI: oai:DiVA.org:kth-357069DiVA, id: diva2:1918001
Conference
OCEANS Conference, April 15-18, 2024, Singapore, Singapore
Note

Part of ISBN 979-8-3503-6207-7

QC 20241204

Available from: 2024-12-04 Created: 2024-12-04 Last updated: 2025-11-17Bibliographically approved
In thesis
1. Relative Navigation for Autonomous Underwater Proximity Operations
Open this publication in new window or tab >>Relative Navigation for Autonomous Underwater Proximity Operations
2025 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis dives into the world of autonomous underwater robotics, specifically oriented at solving the relative navigation problem that arises during an underwater multi-agent proximity operation (prox-op). The present document starts with an introduction to the background theoretical and practical concepts required for the reader to follow the contributions outlined within. We define the concept of proximity operations in the underwater domain and highlight a factor-graph-based robotic state estimation framework used to intuitively model arbitrary prox-ops as Simultaneous Trajectory Estimation and Relative Navigation (STERN) problems. We continue by outlining the attached scientific contributions which carefully address the different elements of the general factor graph representation in a procedural manner: we start by isolating the two navigation-dependent phases of the prox-op and solve them independently; subsequently, we study the full scenario from end to end. The document is redacted such that it provides the story in hindsight surrounding the scientific contributions that are part of this compilation thesis.

Abstract [sv]

Denna avhandling fördjupar sig i världen av autonoma undervattensrobotar, med särskilt fokus på att lösa det relativa navigationsproblemet som uppstår under en undervattensoperation med flera samverkande enheter i närhet (prox-op). Avhandlingen inleds med en introduktion till de teoretiska och praktiska bakgrundskoncept som krävs för att läsaren ska kunna följa de bidrag som presenteras.    Vi definierar begreppet närhetsoperationer inom undervattensdomänen och lyfter fram en faktorgradsbaserad ram för robotars tillståndsuppskattning, som används för att intuitivt modellera godtyckliga prox-ops. Denna ram kallas för Simultaneous Trajectory Estimation and Relative Navigation (STERN). Vi fortsätter med att redogöra för de vetenskapliga bidrag som ingår, vilka metodiskt behandlar de olika elementen i den allmänna faktorgrafsrepresentationen: vi börjar med att isolera de två navigationsberoende faserna i prox-op och löser dem var för sig; därefter studerar vi hela scenariot från början till slut. Avhandlingen är utformat för att i efterhand ge en berättelse kring de vetenskapliga bidragen som ingår i denna sammanläggningsavhandling.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2025. p. xxi, 67
Series
TRITA-SCI-FOU ; 2025:70
Keywords
autonomous underwater vehicles, state estimation, proximity operations, underwater navigation, Autonoma undervattensfarkoster, tillståndsuppskattning, närhetsoperationer, undervattensnavigering
National Category
Robotics and automation
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-372996 (URN)978-91-8106-485-8 (ISBN)
Public defence
2025-12-19, https://kth-se.zoom.us/j/67637947676, F3, Lindstedtsvägen 26, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20251119

Available from: 2025-11-17 Created: 2025-11-17 Last updated: 2025-12-02Bibliographically approved

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Dörner, DavidTerán Espinoza, AldoTorroba, IgnacioKuttenkeuler, JacobStenius, Ivan

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