# The Monado SLAM Dataset for Egocentric Visual-Inertial Tracking

arXiv: https://arxiv.org/abs/2508.00088 · HTML: https://mlsanity.com/paper/2508.00088/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 43 references that are in the map.
- First posted on arXiv 31 Jul 2025.

## Builds on (most cited first, 24 of 24)

- [ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://mlsanity.com/paper/2007.11898/) (2020)
- [TartanAir: A Dataset to Push the Limits of Visual SLAM](https://mlsanity.com/paper/2003.14338/) (2020)
- [Project Aria: A New Tool for Egocentric Multi-Modal AI Research](https://mlsanity.com/paper/2308.13561/) (2023)
- [Robot Operating System 2: Design, Architecture, and Uses In The Wild](https://mlsanity.com/paper/2211.07752/) (2022)
- [Deep Patch Visual Odometry](https://mlsanity.com/paper/2208.04726/) (2022)
- [Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perception](https://mlsanity.com/paper/2306.06362/) (2023)
- [HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videos](https://mlsanity.com/paper/2411.19167/) (2024)
- [Nymeria: A Massive Collection of Multimodal Egocentric Daily Motion in the Wild](https://mlsanity.com/paper/2406.09905/) (2024)
- [LaMAR: Benchmarking Localization and Mapping for Augmented Reality](https://mlsanity.com/paper/2210.10770/) (2022)
- [The TUM VI Benchmark for Evaluating Visual-Inertial Odometry](https://mlsanity.com/paper/1804.06120/) (2018)
- [Visual-Inertial Mapping with Non-Linear Factor Recovery](https://mlsanity.com/paper/1904.06504/) (2019)
- [Aria Everyday Activities Dataset](https://mlsanity.com/paper/2402.13349/) (2024)
- [HoloLens 2 Research Mode as a Tool for Computer Vision Research](https://mlsanity.com/paper/2008.11239/) (2020)
- [Visual-Inertial Monocular SLAM with Map Reuse](https://mlsanity.com/paper/1610.05949/) (2016)
- [OKVIS2: Realtime Scalable Visual-Inertial SLAM with Loop Closure](https://mlsanity.com/paper/2202.09199/) (2022)
- [ADVIO: An authentic dataset for visual-inertial odometry](https://mlsanity.com/paper/1807.09828/) (2018)
- [DM-VIO: Delayed Marginalization Visual-Inertial Odometry](https://mlsanity.com/paper/2201.04114/) (2022)
- [Hilti-Oxford Dataset: A Millimetre-Accurate Benchmark for Simultaneous Localization and Mapping](https://mlsanity.com/paper/2208.09825/) (2022)
- [Recalibrating the KITTI Dataset Camera Setup for Improved Odometry Accuracy](https://mlsanity.com/paper/2109.03462/) (2021)
- [HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry](https://mlsanity.com/paper/2106.11857/) (2021)
- [MIMC-VINS: A Versatile and Resilient Multi-IMU Multi-Camera Visual-Inertial Navigation System](https://mlsanity.com/paper/2006.15699/) (2020)
- [Lighthouse Positioning System: Dataset, Accuracy, and Precision for UAV Research](https://mlsanity.com/paper/2104.11523/) (2021)
- [InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human Navigation](https://mlsanity.com/paper/2411.14358/) (2024)
- [Enhancing Visual Inertial SLAM with Magnetic Measurements](https://mlsanity.com/paper/2409.09904/) (2024)

## Built on by (most cited first, 9 of 9)

- [ECHO: Ego-Centric modeling of Human-Object interactions](https://mlsanity.com/paper/2508.21556/) (2025)
- [VOCA: Visual Odometry with Codec Awareness](https://mlsanity.com/paper/2607.00189/) (2026)
- [Unleashing the Power of Discrete-Time State Representation: Ultrafast Target-based IMU-Camera Spatial-Temporal Calibration](https://mlsanity.com/paper/2509.12846/) (2025)
- [CorVS+: Correspondence-Driven Association of Video Trajectories and Sensors for Identity-Aware Person Localization in Warehouses](https://mlsanity.com/paper/2510.26369/) (2025)
- [Stipple: Real-Time Incremental Gaussian Splatting with Visual-Inertial Tracking](https://mlsanity.com/paper/2608.00931/) (2026)
- [VkVIO: Cross-platform GPU Acceleration for Visual-Inertial Odometry with Vulkan](https://mlsanity.com/paper/2609.30459/) (2026)
- [HexVIO: Towards All-Day Stereo-Inertial Tracking Through Commodity DSPs](https://mlsanity.com/paper/2610.03283/) (2026)
- [RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM](https://mlsanity.com/paper/2610.15157/) (2026)
- [EgoWholeView: Camera-Only Head-Mounted Capture of Body and Bimanual Hand Motion for Embodied Demonstrations](https://mlsanity.com/paper/2610.16256/) (2026)

## Abstract (arXiv)

Humanoid robots and mixed reality headsets benefit from the use of head-mounted sensors for tracking. While advancements in visual-inertial odometry (VIO) and simultaneous localization and mapping (SLAM) have produced new and high-quality state-of-the-art tracking systems, we show that these are still unable to gracefully handle many of the challenging settings presented in the head-mounted use cases. Common scenarios like high-intensity motions, dynamic occlusions, long tracking sessions, low-textured areas, adverse lighting conditions, saturation of sensors, to name a few, continue to be covered poorly by existing datasets in the literature. In this way, systems may inadvertently overlook these essential real-world issues. To address this, we present the Monado SLAM dataset, a set of real sequences taken from multiple virtual reality headsets. We release the dataset under a permissive CC BY 4.0 license, to drive advancements in VIO/SLAM research and development.