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.
Race against the machine: A fully-annotated, open-design dataset of autonomous and piloted high-speed flight,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.