Upload sensor_failure_benchmark dataset (1.4GB, 30770 files)
Browse filesRGB-D 失效对照数据集：24 episodes, MuJoCo backend, 140 frames/episode
This view is limited to 50 files because it contains too many changes. See raw diff
- commercial/acceptance.json +207 -0
- commercial/buyer_brief.md +19 -0
- commercial/coverage.csv +25 -0
- commercial/dataset_card.md +33 -0
- commercial/evaluation_template.csv +25 -0
- commercial/pair_comparison.csv +13 -0
- commercial/quote_assumptions.json +21 -0
- commercial/sample_index.csv +0 -0
- config.json +34 -0
- dataset/README.md +7 -0
- dataset/data/chunk-000/file-000.parquet +3 -0
- dataset/meta/accepted_pairs.json +24 -0
- dataset/meta/episodes/chunk-000/file-000.parquet +3 -0
- dataset/meta/info.json +187 -0
- dataset/meta/input_contract.json +19 -0
- dataset/meta/normalization.json +16 -0
- dataset/meta/quality.json +32 -0
- dataset/meta/scenarios.json +1562 -0
- dataset/meta/splits.json +108 -0
- dataset/meta/stats.json +443 -0
- dataset/meta/tasks.parquet +3 -0
- dataset/videos/observation.images.front_observed/chunk-000/file-000.mp4 +3 -0
- episodes/episode_000000/depth/front/000000.npy +3 -0
- episodes/episode_000000/depth/front/000000.png +3 -0
- episodes/episode_000000/depth/front/000001.npy +3 -0
- episodes/episode_000000/depth/front/000001.png +3 -0
- episodes/episode_000000/depth/front/000002.npy +3 -0
- episodes/episode_000000/depth/front/000002.png +3 -0
- episodes/episode_000000/depth/front/000003.npy +3 -0
- episodes/episode_000000/depth/front/000003.png +3 -0
- episodes/episode_000000/depth/front/000004.npy +3 -0
- episodes/episode_000000/depth/front/000004.png +3 -0
- episodes/episode_000000/depth/front/000005.npy +3 -0
- episodes/episode_000000/depth/front/000005.png +3 -0
- episodes/episode_000000/depth/front/000006.npy +3 -0
- episodes/episode_000000/depth/front/000006.png +3 -0
- episodes/episode_000000/depth/front/000007.npy +3 -0
- episodes/episode_000000/depth/front/000007.png +3 -0
- episodes/episode_000000/depth/front/000008.npy +3 -0
- episodes/episode_000000/depth/front/000008.png +3 -0
- episodes/episode_000000/depth/front/000009.npy +3 -0
- episodes/episode_000000/depth/front/000009.png +3 -0
- episodes/episode_000000/depth/front/000010.npy +3 -0
- episodes/episode_000000/depth/front/000010.png +3 -0
- episodes/episode_000000/depth/front/000011.npy +3 -0
- episodes/episode_000000/depth/front/000011.png +3 -0
- episodes/episode_000000/depth/front/000012.npy +3 -0
- episodes/episode_000000/depth/front/000012.png +3 -0
- episodes/episode_000000/depth/front/000013.npy +3 -0
- episodes/episode_000000/depth/front/000013.png +3 -0
commercial/acceptance.json
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{
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"summary": {
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"product_id": "sensor_failure_benchmark",
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"coverage_split": "matched_conditions",
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"independent_scene_pairs": 12,
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"status": "technical_pass",
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"passed_checks": 7,
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"total_checks": 7,
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"coverage": {
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"expected_cases": 24,
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"observed_cases": 24,
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"complete": true
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},
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"split_counts": {
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"train": 8,
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"validation": 8,
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"test": 8
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},
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"customer_validation": "not_run",
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"review_reasons": [],
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"accepted_recovery_pairs": 22,
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"negative_recoveries": 2,
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"rgb_images": 3360,
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"invalid_label_samples": 0,
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"fully_occluded_or_out_of_view_images": 0,
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"generation_seconds": 182.029
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},
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"checks": [
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{
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"id": "format",
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"label": "数据结构与视频同步",
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"passed": true
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},
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{
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"id": "coverage",
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"label": "实际配置与覆盖计划一致",
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"passed": true
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},
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{
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"id": "split_isolation",
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"label": "完整场景对与种子隔离",
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"passed": true,
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"detail": ""
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},
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{
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"id": "labels",
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"label": "图像及几何标签可读且一致",
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"passed": true
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},
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{
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"id": "sensor_observations",
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"label": "观测与真值分离、文件一致性及观测条件对核验",
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"passed": true
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},
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{
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"id": "observed_faults",
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"label": "指定故障已实际观察到",
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"passed": true
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},
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{
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"id": "verified_recovery",
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"label": "至少包含一条物理验证的恢复正例",
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"passed": true
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}
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],
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"quality": {
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"episodes": 24,
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"frames": 3360,
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"valid_pairs": 22,
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"recovery_success_rate": 0.9166666666666666,
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"failure_coverage": {
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"slip": 6,
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"drop": 6,
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"pose_offset": 6,
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"miss_grasp": 6
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},
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"scenario_coverage": {
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"machine_tending": 12,
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"conveyor_pick": 6,
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"pallet_cell_placement": 6
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},
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"object_shape_coverage": {
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"box": 18,
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"cylinder": 6
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},
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"rejected_pairs": 2,
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"structurally_valid": true,
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"structural_errors": [],
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"physics_validated": true,
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"sensor_model_calibrated": false,
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"real_robot_transfer_tested": false,
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"grasp_candidates": 0,
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"validated_successful_grasps": 0,
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"grasp_physics_validated": false,
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"label_semantics": "depth_gt is geometric camera-z in meters; not measured sensor depth",
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"acceptance": "valid pairs require observed failure, executed recovery, final-state success and physics validation"
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},
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"splits": {
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"method": "paired_scene_group_holdout",
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"coverage_split": "matched_conditions",
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"condition_coverage": {
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"train": [
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"camera_interrupt.challenge",
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"camera_interrupt.reference",
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"compound_shift.challenge",
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"compound_shift.reference",
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"range_noise.challenge",
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| 108 |
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"range_noise.reference",
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"target_missing.challenge",
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"target_missing.reference"
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],
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"validation": [
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"camera_interrupt.challenge",
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| 114 |
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"camera_interrupt.reference",
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| 115 |
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"compound_shift.challenge",
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| 116 |
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"compound_shift.reference",
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| 117 |
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"range_noise.challenge",
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| 118 |
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"range_noise.reference",
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| 119 |
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"target_missing.challenge",
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| 120 |
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"target_missing.reference"
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| 121 |
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],
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"test": [
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| 123 |
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"camera_interrupt.challenge",
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| 124 |
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"camera_interrupt.reference",
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| 125 |
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"compound_shift.challenge",
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| 126 |
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"compound_shift.reference",
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| 127 |
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"range_noise.challenge",
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| 128 |
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"range_noise.reference",
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| 129 |
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"target_missing.challenge",
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| 130 |
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"target_missing.reference"
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| 131 |
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]
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},
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| 133 |
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"independent_scene_pairs": {
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| 134 |
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"train": 4,
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| 135 |
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"validation": 4,
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| 136 |
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"test": 4
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| 137 |
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},
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| 138 |
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"episode_indices": {
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| 139 |
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"train": [
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0,
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1,
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2,
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3,
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4,
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5,
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6,
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7
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],
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"validation": [
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8,
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9,
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10,
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11,
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12,
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13,
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14,
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15
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],
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"test": [
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16,
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17,
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18,
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19,
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20,
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21,
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22,
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| 167 |
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23
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]
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| 169 |
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},
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| 170 |
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"ranges": {
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| 171 |
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"train": "0:8",
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| 172 |
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"validation": "8:16",
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| 173 |
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"test": "16:24"
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| 174 |
+
},
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| 175 |
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"pair_assignments": {
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| 176 |
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"sensor_failure_benchmark.range_noise.train.r000": "train",
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| 177 |
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"sensor_failure_benchmark.target_missing.train.r000": "train",
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| 178 |
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"sensor_failure_benchmark.camera_interrupt.train.r000": "train",
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| 179 |
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"sensor_failure_benchmark.compound_shift.train.r000": "train",
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| 180 |
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"sensor_failure_benchmark.range_noise.validation.r000": "validation",
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| 181 |
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"sensor_failure_benchmark.target_missing.validation.r000": "validation",
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| 182 |
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"sensor_failure_benchmark.camera_interrupt.validation.r000": "validation",
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| 183 |
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"sensor_failure_benchmark.compound_shift.validation.r000": "validation",
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| 184 |
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"sensor_failure_benchmark.range_noise.test.r000": "test",
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| 185 |
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"sensor_failure_benchmark.target_missing.test.r000": "test",
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| 186 |
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"sensor_failure_benchmark.camera_interrupt.test.r000": "test",
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| 187 |
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"sensor_failure_benchmark.compound_shift.test.r000": "test"
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| 188 |
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},
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| 189 |
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"seed_assignments": {
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| 190 |
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"20261024": "train",
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| 191 |
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"20262024": "train",
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| 192 |
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"20263024": "train",
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| 193 |
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"20264024": "train",
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| 194 |
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"20261124": "validation",
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| 195 |
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"20262124": "validation",
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| 196 |
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"20263124": "validation",
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| 197 |
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"20264124": "validation",
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| 198 |
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"20261224": "test",
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| 199 |
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"20262224": "test",
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| 200 |
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"20263224": "test",
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| 201 |
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"20264224": "test"
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| 202 |
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},
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| 203 |
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"group_isolation_verified": true,
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| 204 |
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"scope": "complete-episode split; paired scenes and scene seeds remain isolated when a holdout is used"
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},
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"scope": "technical evidence only; customer model performance and real deployment are not evaluated"
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}
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commercial/buyer_brief.md
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# 机器人 RGB-D 失效对照包 · 客户评估简报
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适用团队：机器人视觉团队、深度补全团队与工位验收负责人
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要解决的任务：现场深度缺测和短时相机中断难以重复，模型升级缺少一致的压力评测。
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预期价值（待客户验证）：保留相同状态、动作与几何真值，交付配对观测、有效像素及实际退化统计。
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| 9 |
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## 客户输入
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| 10 |
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> 流程验证小样：四种条件各自在训练、验证、测试中具备独立种子的场景对；用于分开检查同条件泛化与未知条件压力评测。非真实客户数据。
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## 试点路径
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| 14 |
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先用本样品确认字段、加载和任务匹配，再用固定真实测试集做基线/增量评估；双方确认条件覆盖、验收阈值和用途后报价，只有获得试点评估信号才扩量。
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建议客户补充：相机内参/分辨率、目标物尺寸与材质、实际失败案例、机器人动作定义、模型输入格式、真实测试集和可接受指标。
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| 18 |
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当前技术检查7/7通过，客户效果验证尚未开始。报价假设见quote_assumptions.json；该文件不表示已成交价格或收益承诺。
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commercial/coverage.csv
ADDED
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@@ -0,0 +1,25 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
case_id,pair_id,split,role,scenario_id,object_shape,material,lighting,background,changed_parameter,seed,expected_episodes,observed_episodes,accepted_recovery_pairs,failure_observed,mean_target_image_fraction,matches_plan,issues
|
| 2 |
+
sensor_failure_benchmark.range_noise.train.r000.reference,sensor_failure_benchmark.range_noise.train.r000,train,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20261024,1,1,1,1,0.0042567,True,
|
| 3 |
+
sensor_failure_benchmark.range_noise.train.r000.challenge,sensor_failure_benchmark.range_noise.train.r000,train,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20261024,1,1,1,1,0.0042567,True,
|
| 4 |
+
sensor_failure_benchmark.target_missing.train.r000.reference,sensor_failure_benchmark.target_missing.train.r000,train,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20262024,1,1,1,1,0.00427083,True,
|
| 5 |
+
sensor_failure_benchmark.target_missing.train.r000.challenge,sensor_failure_benchmark.target_missing.train.r000,train,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20262024,1,1,1,1,0.00427083,True,
|
| 6 |
+
sensor_failure_benchmark.camera_interrupt.train.r000.reference,sensor_failure_benchmark.camera_interrupt.train.r000,train,reference,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263024,1,1,1,1,0.00470499,True,
|
| 7 |
+
sensor_failure_benchmark.camera_interrupt.train.r000.challenge,sensor_failure_benchmark.camera_interrupt.train.r000,train,challenge,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263024,1,1,1,1,0.00470499,True,
|
| 8 |
+
sensor_failure_benchmark.compound_shift.train.r000.reference,sensor_failure_benchmark.compound_shift.train.r000,train,reference,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264024,1,1,1,1,0.00417039,True,
|
| 9 |
+
sensor_failure_benchmark.compound_shift.train.r000.challenge,sensor_failure_benchmark.compound_shift.train.r000,train,challenge,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264024,1,1,1,1,0.00417039,True,
|
| 10 |
+
sensor_failure_benchmark.range_noise.validation.r000.reference,sensor_failure_benchmark.range_noise.validation.r000,validation,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20261124,1,1,1,1,0.0041875,True,
|
| 11 |
+
sensor_failure_benchmark.range_noise.validation.r000.challenge,sensor_failure_benchmark.range_noise.validation.r000,validation,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20261124,1,1,1,1,0.0041875,True,
|
| 12 |
+
sensor_failure_benchmark.target_missing.validation.r000.reference,sensor_failure_benchmark.target_missing.validation.r000,validation,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20262124,1,1,1,1,0.00429315,True,
|
| 13 |
+
sensor_failure_benchmark.target_missing.validation.r000.challenge,sensor_failure_benchmark.target_missing.validation.r000,validation,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20262124,1,1,1,1,0.00429315,True,
|
| 14 |
+
sensor_failure_benchmark.camera_interrupt.validation.r000.reference,sensor_failure_benchmark.camera_interrupt.validation.r000,validation,reference,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263124,1,1,1,1,0.00466964,True,
|
| 15 |
+
sensor_failure_benchmark.camera_interrupt.validation.r000.challenge,sensor_failure_benchmark.camera_interrupt.validation.r000,validation,challenge,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263124,1,1,1,1,0.00466964,True,
|
| 16 |
+
sensor_failure_benchmark.compound_shift.validation.r000.reference,sensor_failure_benchmark.compound_shift.validation.r000,validation,reference,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264124,1,1,0,1,0.00379687,True,
|
| 17 |
+
sensor_failure_benchmark.compound_shift.validation.r000.challenge,sensor_failure_benchmark.compound_shift.validation.r000,validation,challenge,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264124,1,1,0,1,0.00379687,True,
|
| 18 |
+
sensor_failure_benchmark.range_noise.test.r000.reference,sensor_failure_benchmark.range_noise.test.r000,test,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20261224,1,1,1,1,0.00429353,True,
|
| 19 |
+
sensor_failure_benchmark.range_noise.test.r000.challenge,sensor_failure_benchmark.range_noise.test.r000,test,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20261224,1,1,1,1,0.00429353,True,
|
| 20 |
+
sensor_failure_benchmark.target_missing.test.r000.reference,sensor_failure_benchmark.target_missing.test.r000,test,reference,machine_tending,box,opaque,studio,studio,sensor_profile,20262224,1,1,1,1,0.00421949,True,
|
| 21 |
+
sensor_failure_benchmark.target_missing.test.r000.challenge,sensor_failure_benchmark.target_missing.test.r000,test,challenge,machine_tending,box,opaque,studio,studio,sensor_profile,20262224,1,1,1,1,0.00421949,True,
|
| 22 |
+
sensor_failure_benchmark.camera_interrupt.test.r000.reference,sensor_failure_benchmark.camera_interrupt.test.r000,test,reference,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263224,1,1,1,1,0.00475186,True,
|
| 23 |
+
sensor_failure_benchmark.camera_interrupt.test.r000.challenge,sensor_failure_benchmark.camera_interrupt.test.r000,test,challenge,conveyor_pick,cylinder,opaque,studio,studio,sensor_profile,20263224,1,1,1,1,0.00475186,True,
|
| 24 |
+
sensor_failure_benchmark.compound_shift.test.r000.reference,sensor_failure_benchmark.compound_shift.test.r000,test,reference,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264224,1,1,1,1,0.00424033,True,
|
| 25 |
+
sensor_failure_benchmark.compound_shift.test.r000.challenge,sensor_failure_benchmark.compound_shift.test.r000,test,challenge,pallet_cell_placement,box,opaque,studio,studio,sensor_profile,20264224,1,1,1,1,0.00424033,True,
|
commercial/dataset_card.md
ADDED
|
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# 机器人 RGB-D 失效对照包 · 数据说明书
|
| 2 |
+
|
| 3 |
+
技术验收：technical_pass。客户实际模型效果与真机迁移：**未验证**。
|
| 4 |
+
|
| 5 |
+
本包包含24条完整episode、3360个时间步、3360张RGB；覆盖24个计划条件，物理验证恢复正例22条。
|
| 6 |
+
|
| 7 |
+
## 使用与评估
|
| 8 |
+
|
| 9 |
+
1. 根据coverage.csv核对条件与实际交付，根据sample_index.csv定位图像与标签。
|
| 10 |
+
2. 使用dataset/meta/splits.json选择完整episode。场景对和种子不跨集合；同类程序化形状可能跨集合。
|
| 11 |
+
3. 仅用train拟合，validation调参，锁定test评估；另用客户真实数据测迁移。
|
| 12 |
+
导出的归一化统计仅由train计算，记录见dataset/meta/normalization.json。
|
| 13 |
+
4. 在evaluation_template.csv填写基线与加入本包后的结果，记录模型版本、真实样本数与验收阈值。
|
| 14 |
+
|
| 15 |
+
参考/挑战样本是可控场景对，不代表已完成因果实验。默认小样用于接口与覆盖评估，不能据此宣称训练规模或泛化效果。
|
| 16 |
+
|
| 17 |
+
三个划分包含相同的条件目录，每个划分使用独立场景种子，完整对照/挑战对保持同组。这用于同条件的种子留出评估，不证明未知物体、工位或退化类型泛化。
|
| 18 |
+
|
| 19 |
+
## 标签与适用边界
|
| 20 |
+
|
| 21 |
+
深度为米制首表面几何真值，非特定传感器实测；法线坐标系见episode。目标掩码像素占整幅图的比例不等于物体可见面比例；完全遮挡/出视野样本作为显式负例保留。感知线action为占位，恢复线为简化三轴夹爪动作。
|
| 22 |
+
|
| 23 |
+
v0.5的sensors/index.jsonl逐条区分受损观测输入与干净真值标签；sensors/report.json报告缺测和误差，并核对观测挑战对的物理轨迹一致性。观测退化没有驱动策略重新执行，不能将原轨迹成功率用作受损观测下的闭环效果。dataset/meta/input_contract.json标明特权真值与建议训练输入。
|
| 24 |
+
|
| 25 |
+
- 默认8条是结构评估样品，不能代表训练规模或真实工况覆盖率。
|
| 26 |
+
- 匹配场景对用于条件比较，不宣称严格物理因果实验。
|
| 27 |
+
- 观测退化为未标定的压力模型，不等同某品牌深度相机。
|
| 28 |
+
- 控制器使用仿真真值；配对行为一致不代表受损观测下闭环策略仍然成功。
|
| 29 |
+
- 训练输入优先使用 observed 图像与 proprioception，物体真值仅作监督或诊断。
|
| 30 |
+
|
| 31 |
+
## 来源和使用约定
|
| 32 |
+
|
| 33 |
+
场景和物体由本项目程序化构建，来源见provenance.json；本说明书不授予独占权或替代双方约定的使用范围。交付前应明确用途、分发范围、客户输入资产来源与支持责任。
|
commercial/evaluation_template.csv
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
case_id,split,metric,baseline_value,augmented_value,real_test_sample_count,customer_acceptance_threshold,notes
|
| 2 |
+
sensor_failure_benchmark.range_noise.train.r000.reference,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 3 |
+
sensor_failure_benchmark.range_noise.train.r000.challenge,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 4 |
+
sensor_failure_benchmark.target_missing.train.r000.reference,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 5 |
+
sensor_failure_benchmark.target_missing.train.r000.challenge,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 6 |
+
sensor_failure_benchmark.camera_interrupt.train.r000.reference,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 7 |
+
sensor_failure_benchmark.camera_interrupt.train.r000.challenge,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 8 |
+
sensor_failure_benchmark.compound_shift.train.r000.reference,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 9 |
+
sensor_failure_benchmark.compound_shift.train.r000.challenge,train,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 10 |
+
sensor_failure_benchmark.range_noise.validation.r000.reference,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 11 |
+
sensor_failure_benchmark.range_noise.validation.r000.challenge,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 12 |
+
sensor_failure_benchmark.target_missing.validation.r000.reference,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 13 |
+
sensor_failure_benchmark.target_missing.validation.r000.challenge,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 14 |
+
sensor_failure_benchmark.camera_interrupt.validation.r000.reference,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 15 |
+
sensor_failure_benchmark.camera_interrupt.validation.r000.challenge,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 16 |
+
sensor_failure_benchmark.compound_shift.validation.r000.reference,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 17 |
+
sensor_failure_benchmark.compound_shift.validation.r000.challenge,validation,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 18 |
+
sensor_failure_benchmark.range_noise.test.r000.reference,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 19 |
+
sensor_failure_benchmark.range_noise.test.r000.challenge,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 20 |
+
sensor_failure_benchmark.target_missing.test.r000.reference,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 21 |
+
sensor_failure_benchmark.target_missing.test.r000.challenge,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 22 |
+
sensor_failure_benchmark.camera_interrupt.test.r000.reference,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 23 |
+
sensor_failure_benchmark.camera_interrupt.test.r000.challenge,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 24 |
+
sensor_failure_benchmark.compound_shift.test.r000.reference,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
| 25 |
+
sensor_failure_benchmark.compound_shift.test.r000.challenge,test,real_task_success_rate,,,,,客户在固定真实测试集上填写；仅训练集可用于拟合
|
commercial/pair_comparison.csv
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
pair_id,split,changed_parameter,reference_value,reference_accepted_recoveries,reference_target_image_fraction,challenge_value,challenge_accepted_recoveries,challenge_target_image_fraction,customer_model_comparison
|
| 2 |
+
sensor_failure_benchmark.range_noise.train.r000,train,sensor_profile,clean,1,0.0042567,depth_noise,1,0.0042567,not_run
|
| 3 |
+
sensor_failure_benchmark.target_missing.train.r000,train,sensor_profile,clean,1,0.00427083,target_dropout,1,0.00427083,not_run
|
| 4 |
+
sensor_failure_benchmark.camera_interrupt.train.r000,train,sensor_profile,clean,1,0.00470499,camera_outage,1,0.00470499,not_run
|
| 5 |
+
sensor_failure_benchmark.compound_shift.train.r000,train,sensor_profile,clean,1,0.00417039,combined,1,0.00417039,not_run
|
| 6 |
+
sensor_failure_benchmark.range_noise.validation.r000,validation,sensor_profile,clean,1,0.0041875,depth_noise,1,0.0041875,not_run
|
| 7 |
+
sensor_failure_benchmark.target_missing.validation.r000,validation,sensor_profile,clean,1,0.00429315,target_dropout,1,0.00429315,not_run
|
| 8 |
+
sensor_failure_benchmark.camera_interrupt.validation.r000,validation,sensor_profile,clean,1,0.00466964,camera_outage,1,0.00466964,not_run
|
| 9 |
+
sensor_failure_benchmark.compound_shift.validation.r000,validation,sensor_profile,clean,0,0.00379687,combined,0,0.00379687,not_run
|
| 10 |
+
sensor_failure_benchmark.range_noise.test.r000,test,sensor_profile,clean,1,0.00429353,depth_noise,1,0.00429353,not_run
|
| 11 |
+
sensor_failure_benchmark.target_missing.test.r000,test,sensor_profile,clean,1,0.00421949,target_dropout,1,0.00421949,not_run
|
| 12 |
+
sensor_failure_benchmark.camera_interrupt.test.r000,test,sensor_profile,clean,1,0.00475186,camera_outage,1,0.00475186,not_run
|
| 13 |
+
sensor_failure_benchmark.compound_shift.test.r000,test,sensor_profile,clean,1,0.00424033,combined,1,0.00424033,not_run
|
commercial/quote_assumptions.json
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"status": "unvalidated_hypothesis",
|
| 3 |
+
"currency": "CNY",
|
| 4 |
+
"product_price_hypothesis": {
|
| 5 |
+
"currency": "CNY",
|
| 6 |
+
"min": 1500,
|
| 7 |
+
"max": 4500,
|
| 8 |
+
"unit": "范围确认后的付费试点",
|
| 9 |
+
"status": "unvalidated",
|
| 10 |
+
"note": "仅用于客户访谈的报价假设，不是市场成交价、自动报价或当前小样售价。"
|
| 11 |
+
},
|
| 12 |
+
"measured_generation_seconds": 182.029,
|
| 13 |
+
"delivered_episodes": 24,
|
| 14 |
+
"delivered_rgb_images": 3360,
|
| 15 |
+
"compute_cost_per_hour": null,
|
| 16 |
+
"human_review_hours": null,
|
| 17 |
+
"customer_integration_hours": null,
|
| 18 |
+
"commercial_acceptance_agreed": false,
|
| 19 |
+
"pricing_basis": "范围、覆盖条件、可用交付和适配工时；原始帧数不等同独立样本数",
|
| 20 |
+
"next_step": "确认客户输入规格和真实评估集后，填写成本、报价与验收条款"
|
| 21 |
+
}
|
commercial/sample_index.csv
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
config.json
ADDED
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"kind": "recovery",
|
| 3 |
+
"backend": "mujoco",
|
| 4 |
+
"name": "RGB-D 失效对照 · 同条件独立种子留出",
|
| 5 |
+
"product_id": "sensor_failure_benchmark",
|
| 6 |
+
"coverage_repeats": 1,
|
| 7 |
+
"coverage_split": "matched_conditions",
|
| 8 |
+
"customer_brief": "流程验证小样：四种条件各自在训练、验证、测试中具备独立种子的场景对；用于分开检查同条件泛化与未知条件压力评测。非真实客户数据。",
|
| 9 |
+
"scenario_id": "machine_tending",
|
| 10 |
+
"object_shape": "box",
|
| 11 |
+
"material": "opaque",
|
| 12 |
+
"background": "studio",
|
| 13 |
+
"lighting": "studio",
|
| 14 |
+
"difficulty": "standard",
|
| 15 |
+
"object_scale": 1.0,
|
| 16 |
+
"object_mass_kg": 0.1,
|
| 17 |
+
"surface_friction": 1.1,
|
| 18 |
+
"camera_jitter": 0.0,
|
| 19 |
+
"sensor_profile": "clean",
|
| 20 |
+
"sensor_severity": 0.5,
|
| 21 |
+
"empirical_sensor_profile": null,
|
| 22 |
+
"episodes": 24,
|
| 23 |
+
"split_strategy": "single_train",
|
| 24 |
+
"frames_per_episode": 140,
|
| 25 |
+
"fps": 20,
|
| 26 |
+
"width": 160,
|
| 27 |
+
"height": 120,
|
| 28 |
+
"seed": 20261024,
|
| 29 |
+
"camera_count": 1,
|
| 30 |
+
"failure_types": [
|
| 31 |
+
"slip"
|
| 32 |
+
],
|
| 33 |
+
"blender_samples": 16
|
| 34 |
+
}
|
dataset/README.md
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# SimForge generated corpus
|
| 2 |
+
|
| 3 |
+
LeRobotDataset v3 Parquet/MP4 layout. Lossless RGB and geometric labels remain in the source episodes.
|
| 4 |
+
|
| 5 |
+
Failed recoveries are labelled negatives, not successful demonstrations. Consult meta/accepted_pairs.json and meta/quality.json.
|
| 6 |
+
|
| 7 |
+
Sensor response and real robot transfer are not validated. RGB video is compressed; use source PNG/NPY for precision labels.
|
dataset/data/chunk-000/file-000.parquet
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:dd5067122b429fb7977ae324d41843728942b439858073f519eb4a146029a0dc
|
| 3 |
+
size 342373
|
dataset/meta/accepted_pairs.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
0,
|
| 3 |
+
1,
|
| 4 |
+
2,
|
| 5 |
+
3,
|
| 6 |
+
4,
|
| 7 |
+
5,
|
| 8 |
+
6,
|
| 9 |
+
7,
|
| 10 |
+
8,
|
| 11 |
+
9,
|
| 12 |
+
10,
|
| 13 |
+
11,
|
| 14 |
+
12,
|
| 15 |
+
13,
|
| 16 |
+
16,
|
| 17 |
+
17,
|
| 18 |
+
18,
|
| 19 |
+
19,
|
| 20 |
+
20,
|
| 21 |
+
21,
|
| 22 |
+
22,
|
| 23 |
+
23
|
| 24 |
+
]
|
dataset/meta/episodes/chunk-000/file-000.parquet
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:116882a6c8eda0f84c96cdb379881f80fb0085617c11049915a5e4910159f196
|
| 3 |
+
size 5258
|
dataset/meta/info.json
ADDED
|
@@ -0,0 +1,187 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"codebase_version": "v3.0",
|
| 3 |
+
"robot_type": "cartesian_parallel_gripper",
|
| 4 |
+
"total_episodes": 24,
|
| 5 |
+
"total_frames": 3360,
|
| 6 |
+
"total_tasks": 3,
|
| 7 |
+
"total_videos": 1,
|
| 8 |
+
"total_chunks": 1,
|
| 9 |
+
"chunks_size": 1000,
|
| 10 |
+
"fps": 20,
|
| 11 |
+
"splits": {
|
| 12 |
+
"train": "0:8",
|
| 13 |
+
"validation": "8:16",
|
| 14 |
+
"test": "16:24"
|
| 15 |
+
},
|
| 16 |
+
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
|
| 17 |
+
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
|
| 18 |
+
"features": {
|
| 19 |
+
"observation.state": {
|
| 20 |
+
"dtype": "float32",
|
| 21 |
+
"shape": [
|
| 22 |
+
10
|
| 23 |
+
],
|
| 24 |
+
"names": null
|
| 25 |
+
},
|
| 26 |
+
"action": {
|
| 27 |
+
"dtype": "float32",
|
| 28 |
+
"shape": [
|
| 29 |
+
5
|
| 30 |
+
],
|
| 31 |
+
"names": null
|
| 32 |
+
},
|
| 33 |
+
"supervision.object_pose": {
|
| 34 |
+
"dtype": "float32",
|
| 35 |
+
"shape": [
|
| 36 |
+
7
|
| 37 |
+
],
|
| 38 |
+
"names": null
|
| 39 |
+
},
|
| 40 |
+
"timestamp": {
|
| 41 |
+
"dtype": "float32",
|
| 42 |
+
"shape": [
|
| 43 |
+
1
|
| 44 |
+
],
|
| 45 |
+
"names": null
|
| 46 |
+
},
|
| 47 |
+
"frame_index": {
|
| 48 |
+
"dtype": "int64",
|
| 49 |
+
"shape": [
|
| 50 |
+
1
|
| 51 |
+
],
|
| 52 |
+
"names": null
|
| 53 |
+
},
|
| 54 |
+
"episode_index": {
|
| 55 |
+
"dtype": "int64",
|
| 56 |
+
"shape": [
|
| 57 |
+
1
|
| 58 |
+
],
|
| 59 |
+
"names": null
|
| 60 |
+
},
|
| 61 |
+
"index": {
|
| 62 |
+
"dtype": "int64",
|
| 63 |
+
"shape": [
|
| 64 |
+
1
|
| 65 |
+
],
|
| 66 |
+
"names": null
|
| 67 |
+
},
|
| 68 |
+
"task_index": {
|
| 69 |
+
"dtype": "int64",
|
| 70 |
+
"shape": [
|
| 71 |
+
1
|
| 72 |
+
],
|
| 73 |
+
"names": null
|
| 74 |
+
},
|
| 75 |
+
"annotation.failure": {
|
| 76 |
+
"dtype": "bool",
|
| 77 |
+
"shape": [
|
| 78 |
+
1
|
| 79 |
+
],
|
| 80 |
+
"names": null
|
| 81 |
+
},
|
| 82 |
+
"annotation.success": {
|
| 83 |
+
"dtype": "bool",
|
| 84 |
+
"shape": [
|
| 85 |
+
1
|
| 86 |
+
],
|
| 87 |
+
"names": null
|
| 88 |
+
},
|
| 89 |
+
"annotation.phase": {
|
| 90 |
+
"dtype": "string",
|
| 91 |
+
"shape": [
|
| 92 |
+
1
|
| 93 |
+
],
|
| 94 |
+
"names": null
|
| 95 |
+
},
|
| 96 |
+
"annotation.failure_type": {
|
| 97 |
+
"dtype": "string",
|
| 98 |
+
"shape": [
|
| 99 |
+
1
|
| 100 |
+
],
|
| 101 |
+
"names": null
|
| 102 |
+
},
|
| 103 |
+
"annotation.scenario_id": {
|
| 104 |
+
"dtype": "string",
|
| 105 |
+
"shape": [
|
| 106 |
+
1
|
| 107 |
+
],
|
| 108 |
+
"names": null
|
| 109 |
+
},
|
| 110 |
+
"annotation.object_shape": {
|
| 111 |
+
"dtype": "string",
|
| 112 |
+
"shape": [
|
| 113 |
+
1
|
| 114 |
+
],
|
| 115 |
+
"names": null
|
| 116 |
+
},
|
| 117 |
+
"annotation.material": {
|
| 118 |
+
"dtype": "string",
|
| 119 |
+
"shape": [
|
| 120 |
+
1
|
| 121 |
+
],
|
| 122 |
+
"names": null
|
| 123 |
+
},
|
| 124 |
+
"annotation.valid_recovery_pair": {
|
| 125 |
+
"dtype": "bool",
|
| 126 |
+
"shape": [
|
| 127 |
+
1
|
| 128 |
+
],
|
| 129 |
+
"names": null
|
| 130 |
+
},
|
| 131 |
+
"annotation.split": {
|
| 132 |
+
"dtype": "string",
|
| 133 |
+
"shape": [
|
| 134 |
+
1
|
| 135 |
+
],
|
| 136 |
+
"names": null
|
| 137 |
+
},
|
| 138 |
+
"annotation.case_id": {
|
| 139 |
+
"dtype": "string",
|
| 140 |
+
"shape": [
|
| 141 |
+
1
|
| 142 |
+
],
|
| 143 |
+
"names": null
|
| 144 |
+
},
|
| 145 |
+
"annotation.pair_id": {
|
| 146 |
+
"dtype": "string",
|
| 147 |
+
"shape": [
|
| 148 |
+
1
|
| 149 |
+
],
|
| 150 |
+
"names": null
|
| 151 |
+
},
|
| 152 |
+
"annotation.variant_role": {
|
| 153 |
+
"dtype": "string",
|
| 154 |
+
"shape": [
|
| 155 |
+
1
|
| 156 |
+
],
|
| 157 |
+
"names": null
|
| 158 |
+
},
|
| 159 |
+
"privileged.simulator_state": {
|
| 160 |
+
"dtype": "float32",
|
| 161 |
+
"shape": [
|
| 162 |
+
23
|
| 163 |
+
],
|
| 164 |
+
"names": null
|
| 165 |
+
},
|
| 166 |
+
"observation.images.front_observed": {
|
| 167 |
+
"dtype": "video",
|
| 168 |
+
"shape": [
|
| 169 |
+
120,
|
| 170 |
+
160,
|
| 171 |
+
3
|
| 172 |
+
],
|
| 173 |
+
"names": [
|
| 174 |
+
"height",
|
| 175 |
+
"width",
|
| 176 |
+
"channels"
|
| 177 |
+
],
|
| 178 |
+
"info": {
|
| 179 |
+
"video.fps": 20,
|
| 180 |
+
"video.codec": "h264",
|
| 181 |
+
"video.pix_fmt": "yuv420p",
|
| 182 |
+
"video.is_depth_map": false,
|
| 183 |
+
"has_audio": false
|
| 184 |
+
}
|
| 185 |
+
}
|
| 186 |
+
}
|
| 187 |
+
}
|
dataset/meta/input_contract.json
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"recommended_policy_inputs": [
|
| 3 |
+
"observation.state",
|
| 4 |
+
"observation.images.front_observed"
|
| 5 |
+
],
|
| 6 |
+
"privileged_simulator_fields": [
|
| 7 |
+
"privileged.simulator_state",
|
| 8 |
+
"supervision.object_pose"
|
| 9 |
+
],
|
| 10 |
+
"label_only_fields": [
|
| 11 |
+
"annotation.*"
|
| 12 |
+
],
|
| 13 |
+
"proprioception_layout": "qpos[0:5] + qvel[0:5]; Cartesian stages and fingers only",
|
| 14 |
+
"path_base": "job_root",
|
| 15 |
+
"observed_depth_index": "sensors/index.jsonl",
|
| 16 |
+
"sensor_calibrated": false,
|
| 17 |
+
"closed_loop_policy_evaluated": false,
|
| 18 |
+
"note": "Policy state contains only Cartesian gripper proprioception. Clean RGB remains outside auto-discovered video features. Commands are generated by an oracle controller; observation degradation is offline. Legacy v0.4 observation.state contained object truth; regenerate for safe defaults."
|
| 19 |
+
}
|
dataset/meta/normalization.json
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"fit_split": "train",
|
| 3 |
+
"episode_indices": [
|
| 4 |
+
0,
|
| 5 |
+
1,
|
| 6 |
+
2,
|
| 7 |
+
3,
|
| 8 |
+
4,
|
| 9 |
+
5,
|
| 10 |
+
6,
|
| 11 |
+
7
|
| 12 |
+
],
|
| 13 |
+
"frame_count": 1120,
|
| 14 |
+
"rgb_source": "lossless source PNG",
|
| 15 |
+
"held_out_observations_used": false
|
| 16 |
+
}
|
dataset/meta/quality.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"episodes": 24,
|
| 3 |
+
"frames": 3360,
|
| 4 |
+
"valid_pairs": 22,
|
| 5 |
+
"recovery_success_rate": 0.9166666666666666,
|
| 6 |
+
"failure_coverage": {
|
| 7 |
+
"slip": 6,
|
| 8 |
+
"drop": 6,
|
| 9 |
+
"pose_offset": 6,
|
| 10 |
+
"miss_grasp": 6
|
| 11 |
+
},
|
| 12 |
+
"scenario_coverage": {
|
| 13 |
+
"machine_tending": 12,
|
| 14 |
+
"conveyor_pick": 6,
|
| 15 |
+
"pallet_cell_placement": 6
|
| 16 |
+
},
|
| 17 |
+
"object_shape_coverage": {
|
| 18 |
+
"box": 18,
|
| 19 |
+
"cylinder": 6
|
| 20 |
+
},
|
| 21 |
+
"rejected_pairs": 2,
|
| 22 |
+
"structurally_valid": true,
|
| 23 |
+
"structural_errors": [],
|
| 24 |
+
"physics_validated": true,
|
| 25 |
+
"sensor_model_calibrated": false,
|
| 26 |
+
"real_robot_transfer_tested": false,
|
| 27 |
+
"grasp_candidates": 0,
|
| 28 |
+
"validated_successful_grasps": 0,
|
| 29 |
+
"grasp_physics_validated": false,
|
| 30 |
+
"label_semantics": "depth_gt is geometric camera-z in meters; not measured sensor depth",
|
| 31 |
+
"acceptance": "valid pairs require observed failure, executed recovery, final-state success and physics validation"
|
| 32 |
+
}
|
dataset/meta/scenarios.json
ADDED
|
@@ -0,0 +1,1562 @@
|
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|
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|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"episode_index": 0,
|
| 4 |
+
"scenario_id": "machine_tending",
|
| 5 |
+
"object_shape": "box",
|
| 6 |
+
"geometry": {
|
| 7 |
+
"shape": "box",
|
| 8 |
+
"half_extents_m": [
|
| 9 |
+
0.022,
|
| 10 |
+
0.022,
|
| 11 |
+
0.035
|
| 12 |
+
],
|
| 13 |
+
"radius_m": null,
|
| 14 |
+
"height_m": 0.07,
|
| 15 |
+
"mass_kg": 0.1,
|
| 16 |
+
"collision_shape": "box",
|
| 17 |
+
"contact_dimension": 4,
|
| 18 |
+
"rolling_friction": null,
|
| 19 |
+
"capsule_long_axis": null
|
| 20 |
+
},
|
| 21 |
+
"scene_parameters": null,
|
| 22 |
+
"commercial_case": {
|
| 23 |
+
"episode_index": 0,
|
| 24 |
+
"case_id": "sensor_failure_benchmark.range_noise.train.r000.reference",
|
| 25 |
+
"condition_id": "range_noise.reference",
|
| 26 |
+
"condition_group_id": "range_noise",
|
| 27 |
+
"coverage_split": "matched_conditions",
|
| 28 |
+
"pair_id": "sensor_failure_benchmark.range_noise.train.r000",
|
| 29 |
+
"split": "train",
|
| 30 |
+
"role": "reference",
|
| 31 |
+
"product_id": "sensor_failure_benchmark",
|
| 32 |
+
"changed_parameter": "sensor_profile"
|
| 33 |
+
},
|
| 34 |
+
"resolved_config": {
|
| 35 |
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| 1525 |
+
"role": "challenge",
|
| 1526 |
+
"product_id": "sensor_failure_benchmark",
|
| 1527 |
+
"changed_parameter": "sensor_profile"
|
| 1528 |
+
},
|
| 1529 |
+
"resolved_config": {
|
| 1530 |
+
"kind": "recovery",
|
| 1531 |
+
"backend": "mujoco",
|
| 1532 |
+
"name": "RGB-D 失效对照 · 同条件独立种子留出",
|
| 1533 |
+
"coverage_split": "condition_holdout",
|
| 1534 |
+
"scenario_id": "pallet_cell_placement",
|
| 1535 |
+
"object_shape": "box",
|
| 1536 |
+
"material": "opaque",
|
| 1537 |
+
"background": "studio",
|
| 1538 |
+
"lighting": "studio",
|
| 1539 |
+
"difficulty": "standard",
|
| 1540 |
+
"object_scale": 1.0,
|
| 1541 |
+
"object_mass_kg": 0.1,
|
| 1542 |
+
"surface_friction": 1.1,
|
| 1543 |
+
"camera_jitter": 0.0,
|
| 1544 |
+
"sensor_profile": "combined",
|
| 1545 |
+
"sensor_severity": 0.5,
|
| 1546 |
+
"empirical_sensor_profile": null,
|
| 1547 |
+
"episodes": 1,
|
| 1548 |
+
"split_strategy": "single_train",
|
| 1549 |
+
"frames_per_episode": 140,
|
| 1550 |
+
"fps": 20,
|
| 1551 |
+
"width": 160,
|
| 1552 |
+
"height": 120,
|
| 1553 |
+
"seed": 20264224,
|
| 1554 |
+
"camera_count": 1,
|
| 1555 |
+
"failure_types": [
|
| 1556 |
+
"miss_grasp"
|
| 1557 |
+
],
|
| 1558 |
+
"blender_samples": 16
|
| 1559 |
+
},
|
| 1560 |
+
"task_instruction": "Recover the box and place it into one pallet cell."
|
| 1561 |
+
}
|
| 1562 |
+
]
|
dataset/meta/splits.json
ADDED
|
@@ -0,0 +1,108 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"method": "paired_scene_group_holdout",
|
| 3 |
+
"coverage_split": "matched_conditions",
|
| 4 |
+
"condition_coverage": {
|
| 5 |
+
"train": [
|
| 6 |
+
"camera_interrupt.challenge",
|
| 7 |
+
"camera_interrupt.reference",
|
| 8 |
+
"compound_shift.challenge",
|
| 9 |
+
"compound_shift.reference",
|
| 10 |
+
"range_noise.challenge",
|
| 11 |
+
"range_noise.reference",
|
| 12 |
+
"target_missing.challenge",
|
| 13 |
+
"target_missing.reference"
|
| 14 |
+
],
|
| 15 |
+
"validation": [
|
| 16 |
+
"camera_interrupt.challenge",
|
| 17 |
+
"camera_interrupt.reference",
|
| 18 |
+
"compound_shift.challenge",
|
| 19 |
+
"compound_shift.reference",
|
| 20 |
+
"range_noise.challenge",
|
| 21 |
+
"range_noise.reference",
|
| 22 |
+
"target_missing.challenge",
|
| 23 |
+
"target_missing.reference"
|
| 24 |
+
],
|
| 25 |
+
"test": [
|
| 26 |
+
"camera_interrupt.challenge",
|
| 27 |
+
"camera_interrupt.reference",
|
| 28 |
+
"compound_shift.challenge",
|
| 29 |
+
"compound_shift.reference",
|
| 30 |
+
"range_noise.challenge",
|
| 31 |
+
"range_noise.reference",
|
| 32 |
+
"target_missing.challenge",
|
| 33 |
+
"target_missing.reference"
|
| 34 |
+
]
|
| 35 |
+
},
|
| 36 |
+
"independent_scene_pairs": {
|
| 37 |
+
"train": 4,
|
| 38 |
+
"validation": 4,
|
| 39 |
+
"test": 4
|
| 40 |
+
},
|
| 41 |
+
"episode_indices": {
|
| 42 |
+
"train": [
|
| 43 |
+
0,
|
| 44 |
+
1,
|
| 45 |
+
2,
|
| 46 |
+
3,
|
| 47 |
+
4,
|
| 48 |
+
5,
|
| 49 |
+
6,
|
| 50 |
+
7
|
| 51 |
+
],
|
| 52 |
+
"validation": [
|
| 53 |
+
8,
|
| 54 |
+
9,
|
| 55 |
+
10,
|
| 56 |
+
11,
|
| 57 |
+
12,
|
| 58 |
+
13,
|
| 59 |
+
14,
|
| 60 |
+
15
|
| 61 |
+
],
|
| 62 |
+
"test": [
|
| 63 |
+
16,
|
| 64 |
+
17,
|
| 65 |
+
18,
|
| 66 |
+
19,
|
| 67 |
+
20,
|
| 68 |
+
21,
|
| 69 |
+
22,
|
| 70 |
+
23
|
| 71 |
+
]
|
| 72 |
+
},
|
| 73 |
+
"ranges": {
|
| 74 |
+
"train": "0:8",
|
| 75 |
+
"validation": "8:16",
|
| 76 |
+
"test": "16:24"
|
| 77 |
+
},
|
| 78 |
+
"pair_assignments": {
|
| 79 |
+
"sensor_failure_benchmark.range_noise.train.r000": "train",
|
| 80 |
+
"sensor_failure_benchmark.target_missing.train.r000": "train",
|
| 81 |
+
"sensor_failure_benchmark.camera_interrupt.train.r000": "train",
|
| 82 |
+
"sensor_failure_benchmark.compound_shift.train.r000": "train",
|
| 83 |
+
"sensor_failure_benchmark.range_noise.validation.r000": "validation",
|
| 84 |
+
"sensor_failure_benchmark.target_missing.validation.r000": "validation",
|
| 85 |
+
"sensor_failure_benchmark.camera_interrupt.validation.r000": "validation",
|
| 86 |
+
"sensor_failure_benchmark.compound_shift.validation.r000": "validation",
|
| 87 |
+
"sensor_failure_benchmark.range_noise.test.r000": "test",
|
| 88 |
+
"sensor_failure_benchmark.target_missing.test.r000": "test",
|
| 89 |
+
"sensor_failure_benchmark.camera_interrupt.test.r000": "test",
|
| 90 |
+
"sensor_failure_benchmark.compound_shift.test.r000": "test"
|
| 91 |
+
},
|
| 92 |
+
"seed_assignments": {
|
| 93 |
+
"20261024": "train",
|
| 94 |
+
"20262024": "train",
|
| 95 |
+
"20263024": "train",
|
| 96 |
+
"20264024": "train",
|
| 97 |
+
"20261124": "validation",
|
| 98 |
+
"20262124": "validation",
|
| 99 |
+
"20263124": "validation",
|
| 100 |
+
"20264124": "validation",
|
| 101 |
+
"20261224": "test",
|
| 102 |
+
"20262224": "test",
|
| 103 |
+
"20263224": "test",
|
| 104 |
+
"20264224": "test"
|
| 105 |
+
},
|
| 106 |
+
"group_isolation_verified": true,
|
| 107 |
+
"scope": "complete-episode split; paired scenes and scene seeds remain isolated when a holdout is used"
|
| 108 |
+
}
|
dataset/meta/stats.json
ADDED
|
@@ -0,0 +1,443 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
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|
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|
|
| 1 |
+
{
|
| 2 |
+
"observation.state": {
|
| 3 |
+
"min": [
|
| 4 |
+
-0.014122764021777623,
|
| 5 |
+
-0.1000000225028425,
|
| 6 |
+
-0.0002008240793322001,
|
| 7 |
+
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dataset/meta/tasks.parquet
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