IRIS: An Immersive Robot Interaction System

RSS 2025 Workshop EgoAct Submission16 Authors

Keywords: Human-Robot Interaction, Extended Reality, Robot Learning: Imitation Learning

Abstract: 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.

Submission Number: 16