Topological Traps Dataset TAU Algorithmic Robotics Fall 2025/2026 Daniel Simanovsky Pre processed occupancy grids and Oracle viability labels derived from the HouseExpo residential floor plan dataset, used to train DanielDDDs/topological traps. Contents Path Description Size data/processed/ 1,001 binary occupancy grids (512x512 px, .npy) ~262 MB data/manifest.csv Train/val/test split (700/150/150), seed 42 <1 MB data/labels/robot 20x15/ Oracle viability labels, small robot ~1 GB data/labels/robot 30x20/ Oracle viability labels, default robot ~1 GB data/labels/robot 40x25/ Oracle viability labels, large robot ~1 GB data/labels/robot 25x18/ Oracle viability labels, unseen test robot ~1 GB Label format Each label file is a (4, 512, 512) uint8 NumPy array. Channel order: [North, South, East, West]. 1 = viable (robot can escape), 0 = directional trap. Robot sizes Size (LxW px) Diagonal (px) Split 20x15 25 Train 30x20 36 Train 40x25 47 Train 25x18 31 Test only (unseen) Oracle algorithm 1. Rotation safe mask: erode free space with circular kernel of diameter sqrt(L^2+W^2) 2. Translation safe masks: erode with oriented rectangular footprint per direction 3. Reverse BFS flood fill: seed rot…
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