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Event-Based Visual-Inertial Odometry on a Fixed-Wing Unmanned Aerial Vehicle
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Event-based cameras are a new type of visual sensor that operate under a unique paradigm. These cameras provide asynchronous data on the log-level changes in light intensity for individual pixels, independent of other pixels measurements. Through the hardware-level approach to change detection, these cameras can achieve microsecond fidelity, millisecond latency, ultra-wide dynamic range, and all with very low power requirements. The advantages provided byevent-based cameras make them excellent candidates for visual odometry for UAVs. A visual odometry pipeline was implemented with a front-end algorithm for generating motion-compensated event-frames feeding a Multi-State Constraint Kalman Filter MSCKF back-end implemented using Scorpion. This pipeline was tested on a public dataset and data collected from an ANT Center UAV flight test.
APPROVED FOR PUBLIC RELEASE