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Enhancing Remote Control Capabilities of ROS-based Robots via 5G Connectivity for Immersive Teleoperation and Object Detection
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-). Polytech Angers, University of Angers, France.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-). Dipartimento di Ingegneria Enzo Ferrari, Universit`a di Modena e Reggio Emilia, Italy.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-). Polytech Angers, University of Angers, France.
2024 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Teleoperation is vital for remote control in hazardous or inaccessible environments, boosting efficiency andsafety. Its evolution has transformed industries, disaster response, and healthcare. Initially used in space exploration andmilitary applications, teleoperation now encompasses fields likemanufacturing, medicine, and deep-sea exploration. Advancesin communication, control systems, and robotics have enhancedits capabilities, enabling precise manipulation and real-timefeedback. Research continues to refine teleoperation, aiming toincrease autonomy, improve user interfaces, and address securityconcerns.In this paper, we propose the use of a teleoperated system,which consists of controlling a robot machine that is capableof moving around city and forest environments thanks to theframework ROS (Robot Operating System), accomplishing thetask of object detection through YOLO algorithm, and providedof cameras that let an operator equipped with a VR headset(Meta Quest 3) to explore the environment from the point ofview of the robot. We also analyze the major challenges that canarise during project implementation. The research’s findings canlead to a better understanding of teleoperated systems and theirimplementation, allowing further researchers to create innovativeand useful projects for the community.

Place, publisher, year, edition, pages
2024.
Keywords [en]
YOLO, ROS2, Object detection, VR Headset
National Category
Computer graphics and computer vision Computer Engineering
Identifiers
URN: urn:nbn:se:miun:diva-51730OAI: oai:DiVA.org:miun-51730DiVA, id: diva2:1877904
Conference
19th Swedish National Computer Networking and Cloud Computing Workshop (SNCNW 2024), Linköping University, Linköping, June 11-12, 2024
Available from: 2024-06-26 Created: 2024-06-26 Last updated: 2025-02-01Bibliographically approved

Open Access in DiVA

fulltext(246 kB)262 downloads
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CiteExportLink to record
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Cite
Citation style
  • apa
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  • de-DE
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  • Other locale
More languages
Output format
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