Multimodal immersive digital twin platform for cyber-physical robot fleets in nuclear environments
robotics
system design
human-robot interaction
nuclear
nuclear facility
Cyber-physical systems
heuristic evaluation
ResearchInstitutes_Networks_Beacons/03/04; name=Energy
ResearchInstitutes_Networks_Beacons/dalton_nuclear_institute; name=Dalton Nuclear Institute
digital twins
moobile robot fleet
DOI:
10.22541/au.169046495.53097561/v2
Publication Date:
2024-02-23T16:06:49Z
AUTHORS (19)
ABSTRACT
AbstractThe nuclear energy sector can benefit from mobile robots for remote inspection and handling, reducing human exposure to radiation. Advances in cyber–physical systems have improved robotic platforms in this sector through digital twin (DT) technology. DTs enhance situational awareness for robot operators, crucial for safety in the nuclear energy sector, and their value is anticipated to increase with the growing complexity of cyber–physical systems. The primary motivation of this work is to rapidly develop and evaluate a robot fleet interface that accounts for these benefits in the context of nuclear environments. Here, we introduce a multimodal immersive DT platform for cyber–physical robot fleets based on the ROS‐Unity 3D framework. The system design enables fleet monitoring and management by integrating building information models, mission parameters, robot sensor data, and multimodal user interaction through traditional and virtual reality interfaces. A modified heuristic evaluation approach, which accounts for the positive and negative aspects of the interface, was introduced to accelerate the iterative design process of our DT platform. Robot operators from leading nuclear research institutions (Sellafield Ltd. and the Japan Atomic Energy Agency) performed a simulated robot inspection mission while providing valuable insights into the design elements of the cyber–physical system. The three usability themes that emerged and inspired our design recommendations for future developers include increasing the interface's flexibility, considering each robot's individuality, and adapting the platform to expand sensor visualization capabilities.
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