AERO-VIS: Asynchronous Event-based Real-time Onboard Visual-Inertial SLAM
Yannick Burkhardt, Sebastián Barbas Laina, Simon Boche, Leonard Freißmuth, Stefan Leutenegger
TLDR
AERO-VIS is an asynchronous, real-time event-inertial SLAM system enabling accurate onboard UAV control and state estimation.
Key contributions
- Presents AERO-VIS, a stereo event-inertial SLAM with an optimized keypoint detector.
- Processes event streams asynchronously for low-latency, real-time performance.
- Achieves unprecedented accuracy in onboard event-based SLAM on UAVs.
- Enables first purely event-based SLAM for closed-loop UAV control and large-scale state estimation.
Why it matters
Event cameras offer robustness in challenging environments, but existing methods often limit performance. AERO-VIS overcomes this by enabling asynchronous processing and achieving high accuracy. This allows for real-time, onboard SLAM and control for UAVs, pushing the boundaries of autonomous systems.
Original 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.
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