# MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality

arXiv: https://arxiv.org/abs/2605.16432 · HTML: https://mlsanity.com/paper/2605.16432/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 49 references that are in the map.
- First posted on arXiv 14 May 2026.

## Builds on (most cited first, 18 of 18)

- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age](https://mlsanity.com/paper/1606.05830/) (2016)
- [Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems](https://mlsanity.com/paper/2106.14386/) (2021)
- [DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams](https://mlsanity.com/paper/1909.12198/) (2019)
- [Swarm-SLAM : Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems](https://mlsanity.com/paper/2301.06230/) (2023)
- [LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments](https://mlsanity.com/paper/2003.01744/) (2020)
- [Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces](https://mlsanity.com/paper/2203.03254/) (2022)
- [Kimera-Multi: a System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping](https://mlsanity.com/paper/2011.04087/) (2020)
- [Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape](https://mlsanity.com/paper/2108.08325/) (2021)
- [LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments](https://mlsanity.com/paper/2205.13135/) (2022)
- [Estimating Uncertain Spatial Relationships in Robotics](https://mlsanity.com/paper/1304.3111/) (2013)
- [A Comparison of Modern General-Purpose Visual SLAM Approaches](https://mlsanity.com/paper/2107.07589/) (2021)
- [Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displays](https://mlsanity.com/paper/1708.03655/) (2017)
- [Virtual, Augmented, and Mixed Reality for Human-Robot Interaction: A Survey and Virtual Design Element Taxonomy](https://mlsanity.com/paper/2202.11249/) (2022)
- [How does Simulation-based Testing for Self-driving Cars match Human Perception?](https://mlsanity.com/paper/2401.14736/) (2024)
- [Spatial Assisted Human-Drone Collaborative Navigation and Interaction through Immersive Mixed Reality](https://mlsanity.com/paper/2402.04070/) (2024)
- [Bridging Research and Practice in Simulation-based Testing of Industrial Robot Navigation Systems](https://mlsanity.com/paper/2510.09396/) (2025)
- [Quest2ROS2: A ROS 2 Framework for Bi-manual VR Teleoperation](https://mlsanity.com/paper/2601.18289/) (2026)

## Abstract (arXiv)

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.