IRIS: An Immersive Robot Interaction System
This addresses the problem of limited reproducibility in XR systems for robotics researchers, though it appears incremental as it builds on existing XR methods.
The paper tackles the challenge of reproducibility and reusability in XR-based robot interaction systems by introducing IRIS, which supports immersive interaction and data collection across diverse simulators and real-world scenarios, demonstrating efficient and intuitive data collection in experiments.
This paper introduces IRIS, an Immersive Robot Interaction System leveraging Extended Reality (XR). Existing XR-based systems enable efficient data collection but are often challenging to reproduce and reuse due to their specificity to particular robots, objects, simulators, and environments. IRIS addresses these issues by supporting immersive interaction and data collection across diverse simulators and real-world scenarios. It visualizes arbitrary rigid and deformable objects, robots from simulation, and integrates real-time sensor-generated point clouds for real-world applications. Additionally, IRIS enhances collaborative capabilities by enabling multiple users to simultaneously interact within the same virtual scene. Extensive experiments demonstrate that IRIS offers efficient and intuitive data collection in both simulated and real-world settings.