XRobot: Workshop on Extended Reality (XR) in Robotics

With the recent advances of AI in the field of robotics, more and more data is needed in order to train foundation models. Extended reality (XR) provides a tool to collect large-scale and realistic data without the requirement of expensive equipment and risks of real-world experiments, while enabling robotic systems to learn from the XR data. This workshop will focus on how XR can support AI-powered robotic applications through simulation, digital twins, immersive teleoperation, and Human-Robot Interaction. The workshop will discuss methods for leveraging XR to collect uni-/multimodal data for safe and efficient robot training. The workshop will also discuss the gaps between XR simulation and real-world robotic applications.  

A Call for Papers is also available, and accepted papers will be submitted for inclusion in the IEEE Xplore Digital Library as part of the conference proceedings published by IEEE Computer Society Press.

Workshop topics: Topics of interest include, but are not limited to:

• XR for large-scale data collection and synthetic dataset generation in robotics

• Simulation-to-reality transfer and closing the sim-to-real gap

• Digital twins for robot design, testing, and deployment

• XR interfaces for immersive teleoperation and remote robot control

• Human-Robot Interaction (HRI) through XR

• Multimodal learning from XR data (e.g., vision, language, tactile, audio)

• Safety, ethics, and reproducibility in XR-based robotics research

• Applications of XR in industrial, medical, service, and educational robotics