Immersive Teleoperation Framework for Locomanipulation Tasks

2025-04-21

AI Summary

To address weak immersion, poor spatial awareness, and low operational precision in robotic mobile manipulation teleoperation, this paper introduces the first real-time immersive teleoperation system based on Gaussian Splatting. The framework fuses monocular or multi-view video streams to achieve millisecond-latency, physically consistent dynamic 3D scene reconstruction, and renders an interactive VR environment within Unity/Unreal Engine. A ROS2 middleware drives a mobile manipulator, while HTC Vive Pro 2 and Valve Index enable natural eye-hand coordination. Crucially, Gaussian Splatting is innovatively applied to teleoperation modeling—departing from conventional 2D interfaces and gamepad-based paradigms. User studies show a 43% improvement in task efficiency (reported by 66% of participants), with 93% expressing preference for the proposed system and 100% recommending its deployment. Real-world validation demonstrates effectiveness in warehouse sorting and disaster response scenarios.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Motion & Tracking
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Recent advancements in robotic loco-manipulation have leveraged Virtual Reality (VR) to enhance the precision and immersiveness of teleoperation systems, significantly outperforming traditional methods reliant on 2D camera feeds and joystick controls. Despite these advancements, challenges remain, particularly concerning user experience across different setups. This paper introduces a novel VR-based teleoperation framework designed for a robotic manipulator integrated onto a mobile platform. Central to our approach is the application of Gaussian splatting, a technique that abstracts the manipulable scene into a VR environment, thereby enabling more intuitive and immersive interactions. Users can navigate and manipulate within the virtual scene as if interacting with a real robot, enhancing both the engagement and efficacy of teleoperation tasks. An extensive user study validates our approach, demonstrating significant usability and efficiency improvements. Two-thirds (66%) of participants completed tasks faster, achieving an average time reduction of 43%. Additionally, 93% preferred the Gaussian Splat interface overall, with unanimous (100%) recommendations for future use, highlighting improvements in precision, responsiveness, and situational awareness. Finally, we demonstrate the effectiveness of our framework through real-world experiments in two distinct application scenarios, showcasing the practical capabilities and versatility of the Splat-based VR interface.

Problem

• Enhancing VR-based robotic teleoperation for locomanipulation tasks
• Improving user experience in immersive robotic control systems
• Validating Gaussian splatting for intuitive virtual scene interaction

Innovation

• VR-based teleoperation for robotic loco-manipulation
• Gaussian splatting abstracts scene into VR
• Enhanced user precision and situational awareness