GHOST in the Robots: Real-Time Exocentric Dual-Robot VR Teleoperation from Onboard Cameras

Robot teleoperation is critical for applications such as remote maintenance, fleet robotics, search and rescue, and data collection for robot learning. Effective teleoperation requires intuitive 3D visualization with reliable depth cues, which conventional screen-based interfaces often fail to provide. We introduce a multi-view VR telepresence system that (1) fuses geometry from three cameras to produce GPU-accelerated point-cloud rendering on standalone VR hardware, and (2) integrates a wrist-mounted RGB stream to provide high-resolution local detail where point-cloud accuracy is limited. Our pipeline supports real-time rendering of approximately 75k points on the Meta Quest 3. A within-subject study was conducted with 31 participants to compare our system to other visualisation modalities, such as RGB streams, a projection of stereo-vision directly in the VR device and point clouds without providing additional RGB information. Across three different teleoperated manipulation tasks, we measured task success, completion time, perceived workload, and usability. Our system achieved the best overall performance, while the Point Cloud modality without RGB also outperforming the RGB streams and OpenTeleVision. These results show that combining global 3D structure with localized high-resolution detail substantially improves telepresence for manipulation and provides a strong foundation for next-generation robot teleoperation systems.

Multi-robot systems that combine the complementary capabilities of specialised platforms are critical for complex missions in challenging, inaccessible environments. Current deployments assign an operator or operator team to each robot, with collaboration relying on operator-to-operator communication to manually coordinate heterogeneous platforms with incompatible interfaces. This operator-dependent approach increases cognitive load and limits scalability across robots from different manufacturers. This study designs and evaluates a shared-visualisation collaborative teleoperation interface to improve operator coordination, situational awareness, and the task performance in multi-operator, multi-robot systems. A comparative user study with 16 participants compared three teleoperation conditions: co-located operators with a shared interface, remote operators with a shared interface, and co-located operators with individual interfaces. Participants controlled two simulated robots in a nuclear power plant digital twin to complete disaster response tasks. Performance metrics, physiological data, and behavioural measures were recorded to assess task performance, cognitive load, and operator awareness across conditions. The co-located shared-interface condition achieved the fastest mission completion (292.8 s), outperforming remote operation (351.6 s) and individual interfaces (385.1 s), with the fewest collisions (0.9 per trial) and highest situational awareness accuracy (91.1 %). Physical co-presence was associated with reduced cognitive load, with NASA-TLX scores increasing from 38.2 in co-located to 57.7 in remote operation, supported by consistent physiological indicators. These results demonstrate that co-presence and shared interfaces provide complementary benefits, supporting workload regulation and mutual awareness respectively in multi-operator, multi-robot teleoperation.

Multi-operator control of robot teams requires not only access to the same mission information, but also mechanisms for maintaining shared awareness and preventing conflicting interventions. Building on our previous HORUS interface (Holistic Operational Reality for Unified Systems) we present a mixed-reality interface that extends single-operator multi-robot supervision to collaborative multi-operator use. The system supports two complementary modes: a co-located shared workspace, in which operators observe and manipulate the same mini-map in the same physical location, and a private-workspace mode, in which operators work on the same mission through independently placed local workspaces. The architecture combines registration-driven scene construction, lightweight shared-session synchronization, and per-robot control leases to support collaborative monitoring, tasking, and teleoperation while preventing conflicting commands. We evaluated the approach in a human-subject study with 36 participants (18 pairs) controlling three Nova Carter mobile robots in two search environments. The performance of the objective task was comparable across the two modes, indicating that both modes supported effective mission execution. However, the co-located shared workspace significantly improved perceived collaboration, shared understanding, and handoff clarity, and was the preferred collaborative mode. These results indicate that physically co-locating the MR workspace improves how operators coordinate even when the underlying robot-control tools remain unchanged.