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Evaluating Graphical User Interfaces for Improving Depth Perception with Remote Crane Operators
Norwegian University of Science & Technology (NTNU), Department of Design, Trondheim, Norway.
LuleƄ University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
2024 (English)In: Proceedings - 2024 IEEE 48th Annual Computers, Software, and Applications Conference, COMPSAC 2024 / [ed] Shahriar H.; Ohsaki H.; Sharmin M.; Towey D.; Majumder AKM.J.A.; Hori Y.,;Yang J.-J.; Takemoto M.; Sakib N.; Banno R.,; Ahamed S.I., IEEE, 2024, p. 640-649Conference paper, Published paper (Refereed)
Abstract [en]

Container cranes are traditionally operated by operators who work inside the crane's cabin. Nowadays, there are also container cranes that can be operated remotely from control rooms. The change from on-site operation to remote operation introduced a new problem called the lack of depth perception. Operators of remote container cranes rely on the video stream shown on their monitors to see the remote environment, but it is more difficult to estimate the distance between existing objects based on the view on flat screens. The lack of depth perception could increase the risk of collisions since it reduces operators' capability to lift and stack containers accurately. This paper proposes three types of graphical user interfaces (GUIs) that could improve depth perception in remote crane operation. The first GUI visualizes the shadow of the crane's spreader or the container, while the second GUI shows four perspective lines from each edge of the crane's spreader or the container. The third GUI provides the x-ray vision, which highlights the edges of the container and makes the container semi-transparent. We involved seven remote crane operators in an experiment, where they had to move ten containers while using either of the proposed GUIs and without using any additional support. The results suggest that the shadow interface and the line interface provided better outcomes than the condition without having any additional support in terms of completion time, stacking accuracy, number of collisions, as well as perceived workload and usability.

Place, publisher, year, edition, pages
IEEE, 2024. p. 640-649
Keywords [en]
graphical user interface, remote operation, crane, depth perception
National Category
Robotics and automation Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-110134DOI: 10.1109/COMPSAC61105.2024.00092ISI: 001308581200083Scopus ID: 2-s2.0-85204032439OAI: oai:DiVA.org:ltu-110134DiVA, id: diva2:1907736
Conference
48th IEEE International Conference on Computers, Software, and Applications (COMPSAC 2024), Osaka, Japan, July 2-4, 2024
Note

ISBN for host publication: ISBN 979-8-3503-7696-8;

Available from: 2024-10-23 Created: 2024-10-23 Last updated: 2025-10-21Bibliographically approved

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