# Visual-Inertial Odometry of Aerial Robots

arXiv: https://arxiv.org/abs/1906.03289 · HTML: https://mlsanity.com/paper/1906.03289/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2019.

## Built on by (most cited first, 14 of 14)

- [FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking Datasets](https://mlsanity.com/paper/2302.12772/) (2023)
- [Avoiding Degeneracy for Monocular Visual SLAM with Point and Line Features](https://mlsanity.com/paper/2103.01501/) (2021)
- [Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry](https://mlsanity.com/paper/2209.06588/) (2022)
- [Continuous Pose for Monocular Cameras in Neural Implicit Representation](https://mlsanity.com/paper/2311.17119/) (2023)
- [Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning](https://mlsanity.com/paper/2109.14974/) (2021)
- [Low Latency Visual Inertial Odometry with On-Sensor Accelerated Optical Flow for Resource-Constrained UAVs](https://mlsanity.com/paper/2406.13345/) (2024)
- [ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion](https://mlsanity.com/paper/2105.05600/) (2021)
- [Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)](https://mlsanity.com/paper/2112.13018/) (2021)
- [RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry](https://mlsanity.com/paper/2203.07162/) (2022)
- [Event-based Sensor Fusion and Application on Odometry: A Survey](https://mlsanity.com/paper/2410.15480/) (2024)
- [A 2.5D Vehicle Odometry Estimation for Vision Applications](https://mlsanity.com/paper/2105.02679/) (2021)
- [The Use of Multi-Scale Fiducial Markers To Aid Takeoff and Landing Navigation by Rotorcraft](https://mlsanity.com/paper/2309.08769/) (2023)
- [NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments](https://mlsanity.com/paper/2506.18689/) (2025)
- [A Simple yet Effective Subway Self-positioning Method based on Aerial-view Sleeper Detection](https://mlsanity.com/paper/2410.09492/) (2024)

## Abstract (arXiv)

Visual-Inertial odometry (VIO) is the process of estimating the state (pose and velocity) of an agent (e.g., an aerial robot) by using only the input of one or more cameras plus one or more Inertial Measurement Units (IMUs) attached to it. VIO is the only viable alternative to GPS and lidar-based odometry to achieve accurate state estimation. Since both cameras and IMUs are very cheap, these sensor types are ubiquitous in all today's aerial robots.