MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality
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arXiv
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| Format: | Preprint |
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2026
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| author | Aryan, Prakash Erdogdu, Cem Kumarchokkappan, Kavinaya Kehrer, Timo Panichella, Sebastiano |
| author_facet | Aryan, Prakash Erdogdu, Cem Kumarchokkappan, Kavinaya Kehrer, Timo Panichella, Sebastiano |
| contents | Operating a multi-robot fleet for simultaneous localization and mapping (SLAM) in applications such as building inspection or warehouse-aisle monitoring requires the operator to maintain spatial awareness of each robot's position and mapping state, a task that scales poorly on conventional 2D interfaces. We present MR-SLAM, a mixed reality (MR) system in which an operator wearing a Meta Quest 3 headset teleoperates three simulated TurtleBot3 robots through a passthrough view with real-world occlusion, while spatially anchored dashboard panels report mapping progress in situ. Each robot runs an independent SLAM Toolbox instance whose occupancy grid is merged in real time on a Robot Operating System 2 (ROS 2) back end. Across five 9-minute evaluation sessions, the system delivered scans at 8.83 +/- 0.16 Hz, mapped 17.9 +/- 0.8 m^2 of merged occupancy, and reached 94.7 +/- 0.5% cross-instance occupancy consistency across robot pairs. An additional session recorded 6.3 ms median transform jitter and 26.7 m^2 coverage of a 41 m^2 grid. We position MR-SLAM as a reference implementation for combining passthrough mixed reality supervision with multi-robot SLAM on consumer hardware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_16432 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality Aryan, Prakash Erdogdu, Cem Kumarchokkappan, Kavinaya Kehrer, Timo Panichella, Sebastiano Robotics Artificial Intelligence Human-Computer Interaction Operating a multi-robot fleet for simultaneous localization and mapping (SLAM) in applications such as building inspection or warehouse-aisle monitoring requires the operator to maintain spatial awareness of each robot's position and mapping state, a task that scales poorly on conventional 2D interfaces. We present MR-SLAM, a mixed reality (MR) system in which an operator wearing a Meta Quest 3 headset teleoperates three simulated TurtleBot3 robots through a passthrough view with real-world occlusion, while spatially anchored dashboard panels report mapping progress in situ. Each robot runs an independent SLAM Toolbox instance whose occupancy grid is merged in real time on a Robot Operating System 2 (ROS 2) back end. Across five 9-minute evaluation sessions, the system delivered scans at 8.83 +/- 0.16 Hz, mapped 17.9 +/- 0.8 m^2 of merged occupancy, and reached 94.7 +/- 0.5% cross-instance occupancy consistency across robot pairs. An additional session recorded 6.3 ms median transform jitter and 26.7 m^2 coverage of a 41 m^2 grid. We position MR-SLAM as a reference implementation for combining passthrough mixed reality supervision with multi-robot SLAM on consumer hardware. |
| title | MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality |
| topic | Robotics Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2605.16432 |