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  "documentTitle": "2023 Air Street Capital The State of AI Report 2023",
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      "text": "This is a first time win for a robot in a competitive sport (first-person view drone racing).",
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      "text": "Swift uses a combination of learning-based and more traditional techniques. It combines a VIO estimator with a gate detector that estimates global position and orientation of the drone through a Kalman filter to obtain an accurate estimation of the robot’s state.\nSwift’s policy is trained using on-policy model-free deep reinforcement learning in simulation with a reward that combines progress towards the next gate and keeping it in the field of view (this increases pose estimation accuracy). The racing policy transfers well from sim to real when accounting for uncertainty in perception.",
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      "text": "This is a first time win for a robot in a competitive sport (first-person view drone racing). Swift is an autonomous system that can race a quadrotor at the level of human world champions using only onboard sensors and computation. It won several races against 3 champions and had the fastest recorded time.",
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