kth.sePublications KTH
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
SMaRCSim: Maritime Robotics Simulation Modules
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-8264-611X
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Aerospace, moveability and naval architecture.ORCID iD: 0000-0002-8738-1576
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-5656-0259
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-7714-928X
Show others and affiliations
2025 (English)In: 2025 Symposium on Maritime Informatics and Robotics, MARIS 2025, Institute of Electrical and Electronics Engineers (IEEE) , 2025Conference paper, Published paper (Refereed)
Abstract [en]

Developing new functionality for underwater robots and testing them in the real world is time-consuming and resource-intensive. Simulation environments allow for rapid testing before field deployment. However, existing tools lack certain functionality for use cases in our project: i) developing learning-based methods for underwater vehicles; ii) creating teams of autonomous underwater, surface, and aerial vehicles; iii) integrating the simulation with mission planning for field experiments. A holistic solution to these problems presents great potential for bringing novel functionality into the underwater domain. In this paper we present SMaRCSim, a set of simulation packages that we have developed to help us address these issues.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025.
Keywords [en]
AUVs, learning-based methods, mission-planning, multi-domain, Simulation
National Category
Robotics and automation Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-372338DOI: 10.1109/MARIS64137.2025.11139391Scopus ID: 2-s2.0-105017856929OAI: oai:DiVA.org:kth-372338DiVA, id: diva2:2011909
Conference
2025 Symposium on Maritime Informatics and Robotics, MARIS 2025, Syros, Greece, June 26-27, 2025
Note

Part of ISBN 9798331513108

QC 20251106

Available from: 2025-11-06 Created: 2025-11-06 Last updated: 2025-11-06Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Kartašev, MartDörner, DavidÖzkahraman, ÖzerÖgren, PetterStenius, IvanFolkesson, John

Search in DiVA

By author/editor
Kartašev, MartDörner, DavidÖzkahraman, ÖzerÖgren, PetterStenius, IvanFolkesson, John
By organisation
Robotics, Perception and Learning, RPLAerospace, moveability and naval architecture
Robotics and automationComputer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 51 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf