AERO-VIS: Asynchronous Event-based Real-time Onboard Visual-Inertial SLAM

Abstract:The robustness of event cameras to high dynamic range and motion blur holds the potential to improve visual odometry systems in challenging environments. Although their high temporal resolution does not require synchronous processing, most event-based odometry methods still run at fixed rates, which simplifies system design but restricts latency and throughput. In this work, we present AERO-VIS, a stereo event-inertial SLAM system with an integrated, data-driven, robust, and performance-optimized keypoint detector. By decoupling event preprocessing from state estimation, our architecture operates asynchronously at the maximum rate supported by available hardware, dynamically adapting to downstream runtime demands and ensuring low-latency, real-time performance. When deploying AERO-VIS on a UAV, we achieve unprecedented accuracy in onboard event-based SLAM. These unique characteristics enable us to present the first purely event-based inertial SLAM system that demonstrates closed-loop UAV control and large-scale state estimation while relying solely on onboard compute. Videos of the experiments, source code, and additional results are available at this https URL.

Robotics (cs.RO)

arXiv:2605.07885 [cs.RO]

(or arXiv:2605.07885v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2605.07885 Focus to learn more arXiv-issued DOI via DataCite

IEEE Robotics and Automation Letters, vol. 11, no. 10, pp. 11689-11696, Oct. 2026

https://doi.org/10.1109/LRA.2026.3726392 Focus to learn more DOI(s) linking to related resources

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.