[2605.16432] MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality
[Submitted on 14 May 2026]
Title:MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality
View a PDF of the paper titled MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality, by Prakash Aryan and 4 other authors
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Abstract: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.
Comments: Accepted to ICRA 2026 Workshop "MM-SpatialAI Workshop: Multi-Modal Spatial AI for Robust Navigation and Open-World Understanding"
Subjects:
Robotics (cs.RO); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2605.16432 [cs.RO]
(or arXiv:2605.16432v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2605.16432
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Prakash Aryan [view email] [v1] Thu, 14 May 2026 20:35:59 UTC (37,958 KB)
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