Immersive Teleoperation of Adaptive Mobile Robots: Evaluating Human Factors and Network Resilience in Mixed Reality

Abstract

Efficient robotic teleoperation for industrial inspection requires interfaces that maximize intuitive control and situational awareness. While traditional mixed reality (MR) systems offer alternatives, standard controller-based methods lack environment customization and demand external peripheral hardware. This study introduces a peripheral-hardware-free, customizable 3D spatial virtual cockpit application deployed on a Meta Quest 3 headset for long-distance, non-line-of-sight teleoperation of the Improbability Roller-2, a mobile robotic platform that dynamically adjusts its wheel geometry to traverse varied terrain over a Virtual Private Network (VPN). The system’s novel spatial cockpit architecture allows operators to scale multi-channel parameters dynamically without relying on physical hardware controllers. The framework was evaluated using transmission-quality benchmarks, an active industrial machine shop deployment, and a 20-participant user study assessing usability and cognitive load. Experimental results yielded a mean System Usability Scale (SUS) score of 82.75, corresponding to an excellent usability rating, and a low mean operator workload, with a NASA Task Load Index (NASA-TLX) score of 5.19 out of 21. Participants also rated the workspace customization feature positively, assigning it a rating of 4.6 out of 5. In terms of communication performance, the system successfully completed all inspection tasks even under severely degraded VPN conditions. These findings demonstrate that the proposed customizable 3D spatial interface provides a robust, scalable alternative to traditional controller-based setups for long-distance remote robotic inspection in real-world industrial settings.