Yonder: A 4.65M Frame Drone Perspective Dataset for Indoor Navigation The cross simulator generalization gap. Yonder is the largest publicly available drone perspective dataset for indoor navigation, plus a closed loop benchmark designed to expose a failure mode invisible to standard offline metrics: perception trained on one simulator does not transfer cleanly to a different simulator, even when both target the same task. This dataset accompanies the NeurIPS 2026 Datasets & Benchmarks submission: "Yonder: A 4.65M Frame Drone Navigation Dataset and the Cross Simulator Generalization Gap." Headline numbers (paper subset) 4,650,324 drone perspective frames 387,527 waypoint NPZ files (one per waypoint × 12 yaws) 167 indoor 3D environments (all from HSSD, all with semantic annotations) 52 sensor arrays per NPZ (stereo RGB, depth, IR, LiDAR 360, semantic segmentation, pose, IMU) ~3.3 TB total What's in a waypoint Every waypoint NPZ contains a single drone pose with 12 yaw orientations . For each yaw: Sensor Resolution / Format Left RGB 640×480, uint8 Right RGB 640×480, uint8 Forward depth 640×480, float16 (meters) Landing camera 640×480, uint8 (downward) Up IR / Down IR 640×480, uint8 L…
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