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

TL;DR

AERO-VIS is a novel asynchronous event-based stereo SLAM system with integrated keypoint detection, enabling real-time onboard UAV navigation with high accuracy using only onboard computation.

Contribution

It introduces the first purely event-based inertial SLAM system that processes data asynchronously for low latency and demonstrates closed-loop UAV control.

Findings

Achieves unprecedented accuracy in onboard event-based SLAM.

Enables closed-loop UAV control using solely onboard compute.

Demonstrates large-scale state estimation in real-time.

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 processing the event stream asynchronously, the system dynamically adapts to downstream runtime demands, ensuring low-latency and 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. A video of the experiments and the source code are available at ethz-mrl.github.io/AERO-VIS.