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A Consistent Dataset for Dynamic Underwater Proximity Operations
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0003-2336-9401
Institute of Technology, Department of Aeronautics and Astronautics Massachusetts, Cambridge, USA.ORCID iD: 0009-0001-5655-1501
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0002-1090-9168
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0009-0006-9655-4156
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2025 (English)In: OCEANS 2025 Brest, OCEANS 2025, Institute of Electrical and Electronics Engineers (IEEE) , 2025Conference paper, Published paper (Refereed)
Abstract [en]

Open data are scarce in underwater robotics, making it more difficult for researchers to develop new methods that address real-world problems. In this work, we present the experimental design, execution, and curation of three datasets that represent different conditions in a realistic underwater dynamic proximity operation. The raw datasets gathered during the deployments are post-processed to improve consistency. We detail and use a joint batch optimization technique that uses a probabilistic approach to iteratively search for the set of optimal agent trajectories that are in best agreement with the relative measurements provided by a USBL positioning system and optical pose measurements from a fiducial light array. Error analysis of the relative measurements with respect to the baseline and optimized trajectories validate our results, effectively providing ground-truth trajectories of the agents. The resulting datasets, together with their documentation, are publicly available at github.com/aldoteran/asko_2024_datasets

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025.
Keywords [en]
autonomous underwater vehicles, proximity operations, relative navigation, state estimation, underwater docking
National Category
Robotics and automation Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-370688DOI: 10.1109/OCEANS58557.2025.11104553ISI: 001565320000164Scopus ID: 2-s2.0-105015036620OAI: oai:DiVA.org:kth-370688DiVA, id: diva2:2002184
Conference
OCEANS 2025 Brest, OCEANS 2025, Brest, France, June 16-19, 2025
Note

Part of ISBN 9798331537470

QC 20250930

Available from: 2025-09-30 Created: 2025-09-30 Last updated: 2025-12-05Bibliographically 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)
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Note

QC 20251119

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

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Terán Espinoza, AldoDeutsch, ClemensRolleberg, NiklasFolkesson, JohnSigray, PeterKuttenkeuler, Jacob

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Terán Espinoza, AldoEspinoza, Antonio TeránDeutsch, ClemensRolleberg, NiklasFolkesson, JohnSigray, PeterKuttenkeuler, Jacob
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