File size: 2,236 Bytes
b7d1a0a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | schema_version: '1.0'
category: b
name: stacking_blocks_ordered
description: 'Identical scene to Category A: three blocks (red, green, blue) on the
black mat, a magenta cross on the white mat. The instruction states the bottom-to-top
order explicitly.'
instruction_templates:
all_episodes: Stack the blocks from the black mat to the white mat at the cross
position, with order from bottom to top of {c1}, {c2}, {c3} blocks.
tasks:
1:
episodes: 60
order: red-green-blue
instruction: Stack the blocks from the black mat to the white mat at the cross
position, with order from bottom to top of red, green, blue blocks.
2:
episodes: 60
order: blue-green-red
instruction: Stack the blocks from the black mat to the white mat at the cross
position, with order from bottom to top of blue, green, red blocks.
3:
episodes: 60
order: green-red-blue
instruction: Stack the blocks from the black mat to the white mat at the cross
position, with order from bottom to top of green, red, blue blocks.
4:
episodes: 60
order: red-blue-green
instruction: Stack the blocks from the black mat to the white mat at the cross
position, with order from bottom to top of red, blue, green blocks.
trained_orders:
- red-green-blue
- blue-green-red
- green-red-blue
- red-blue-green
held_out_orders:
- blue-red-green
- green-blue-red
held_out_episodes: 0
randomization:
cross_center:
region: centred square of side 0.1 m on the white mat
white_mat_center:
- 0.25
- -0.135
distribution: uniform
block_xy:
region: black mat, inset by SPAWN_MARGIN
black_mat_center:
- 0.25
- 0.135
half_extent:
- 0.077
- 0.067
min_center_gap_m: 0.07
distribution: uniform with rejection; whole set resampled if stranded
sampled_in: canonical color order (red, green, blue, yellow)
block_yaw_rad:
- -0.7853981633974483
- 0.7853981633974483
seed_formula: seed = 100_000_000*category_code + 1_000_000*task_id + episode_id +
10_000*attempt, category_code = {a:1, b:2, c:3}; rng = numpy.random.default_rng(seed)
split_rule: episode_id % 10 == 0 -> val, else train
|