A dual pose-graph architecture for drone racing localization reduces trajectory error by 56-74% over visual-inertial odometry and outperforms single-graph versions by 10-12% at the same speed.
SVO: Fast semi-direct monocular visual odometry,
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Dual Pose-Graph Semantic Localization for Vision-Based Autonomous Drone Racing
A dual pose-graph architecture for drone racing localization reduces trajectory error by 56-74% over visual-inertial odometry and outperforms single-graph versions by 10-12% at the same speed.