Reality Fusion: Robust Real-time Immersive Mobile Robot Teleoperation with Volumetric Visual Data Fusion

Abstract-- We introduce Reality Fusion, a novel robot teleoperation system that localizes, streams, projects, and merges a typical onboard depth sensor with a photorealistic, high resolution, high framerate, and wide FoV rendering of the complex remote environment represented as 3D Gaussian splats (3DGS). Our framework enables robust egocentric and exocentric robot teleoperation in immersive VR, with the 3DGS effectively extending spatial information of a depth sensor with limited FoV and balancing the trade-off between data streaming costs and data visual quality. We evaluated our framework through a user study with 24 participants, which revealed that Reality Fusion leads to significantly better user performance, situation awareness, and user preferences. I. INTRODUCTION In recent years, the rapid development of extended reality feedback through low-cost sensor setups such as a single (XR) technology has presented enormous opportunities 2D video camera or a single stereo depth camera. The sensors often capture visual information with a restricted possibility to display 3D spatial cues about the robot's field of view (FoV), which hinders users from observing environment to the operators through an immersive headmounted the remote environment from obscured angles and therefore display (HMD) enables a remote "telepresence" restricts them from establishing a concrete mental model of experience that has the potential to significantly improve the robot's surroundings. However, building a robust In this work, we propose Reality Fusion, a novel immersive real-time immersive robot teleoperation system is still faced robot teleoperation framework that implements a with many technical challenges.