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Upload sensor_failure_benchmark dataset (1.4GB, 30770 files) (part 37)

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provenance.json ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "application": "simforge-workshop",
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+ "version": "0.6.0",
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+ "parent_job_id": null,
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+ "generated_at": "2026-10-23T09:37:24.523518+00:00",
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+ "name": "RGB-D 失效对照 · 同条件独立种子留出",
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+ "product_id": "sensor_failure_benchmark",
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+ "coverage_repeats": 1,
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+ "coverage_split": "matched_conditions",
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+ "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。",
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+ "scenario_id": "machine_tending",
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+ "background": "studio",
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+ },
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+ "production_plan": "production_plan.json",
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+ "production_plan_sha256": "f55a84aa67c56fbdc3e4f43af544bb1763ee7bf05553a87a918b69dbdaadd459",
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+ "training_readiness": "training_readiness.json",
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+ "sensor_report": "sensors/report.json",
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+ "sensor_calibrated": false,
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+ "input_contract": "dataset/meta/input_contract.json",
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+ "upstream_sources": {
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+ "schema_version": 1,
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+ "acquired_at": "2026-10-22T11:22:49.839268+00:00",
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+ "notes": [
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+ "Source snapshots only; clone is not installation or execution.",
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+ "Existing trees are not reset, pulled, deleted or updated.",
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+ "Each asset and dependency license requires separate review."
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+ ],
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+ "sources": [
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+ {
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+ "name": "FailSafe",
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+ "url": "https://github.com/Jimntu/FailSafe_code.git",
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+ "license": "MIT",
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+ "role": "ManiSkill failure/recovery reference implementation",
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+ "windows_sparse_paths": [
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+ "assets",
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+ "data",
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+ "examples",
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+ "failgen",
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+ "ManiSkill/mani_skill",
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+ "ManiSkill/examples"
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+ ],
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+ "status": "existing",
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+ "path": "external/FailSafe",
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+ "commit": "b863aaecc50407a769c191f67d79ddfaab9f6880",
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+ "licenses": [
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+ {
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+ "path": "LICENSE",
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+ "sha256": "f5ca7719dacf332c7cc5d007044cce3146e919bf1a8ca1effe9926d681335b0e"
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+ }
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+ ],
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+ "lfs_payloads_downloaded": false,
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+ "checkout_scope": "Windows sparse source checkout; benchmark documentation excluded",
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+ "working_tree_dirty": false
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+ },
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+ {
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+ "name": "BlenderProc",
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+ "url": "https://github.com/DLR-RM/BlenderProc.git",
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+ "license": "GPL-3.0",
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+ "role": "Blender-based rendering and annotation reference pipeline",
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+ "status": "existing",
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+ "path": "external/BlenderProc",
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+ "commit": "76bd8b82ee19489843578ff045298642197bf883",
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+ "licenses": [
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+ {
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+ "path": "LICENSE",
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+ "sha256": "0b383d5a63da644f628d99c33976ea6487ed89aaa59f0b3257992deac1171e6b"
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+ }
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+ ],
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+ "lfs_payloads_downloaded": false,
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+ "checkout_scope": "default tracked tree",
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+ "working_tree_dirty": false
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+ },
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+ {
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+ "name": "RoboTwin",
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+ "url": "https://github.com/RoboTwin-Platform/RoboTwin.git",
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+ "license": "MIT",
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+ "role": "Bimanual operation data generation reference implementation",
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+ "status": "existing",
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+ "path": "external/RoboTwin",
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+ "commit": "ea8b21121ebb3cd201ff5b3fe361944ac94eda3f",
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+ "licenses": [
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+ {
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+ "path": "LICENSE",
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+ "sha256": "2aa88b4e1d3257a210a516ad3df3d7f322d03c4285e432d35976980cdb9622fa"
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+ }
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+ ],
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+ "lfs_payloads_downloaded": false,
114
+ "checkout_scope": "default tracked tree",
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+ "working_tree_dirty": false
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+ }
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+ ]
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+ },
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+ "assets": "procedurally authored by this project; no TransFrag27K/MimicGen assets used",
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+ "real_robot_transfer_tested": false
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+ }
sensors/README.md ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # RGB-D 观测压力数据
2
+
3
+ 本包把当前时刻的干净 RGB/几何深度/目标掩码作为监督目标,另存受损观测作为输入。噪声、目标区域缺测和短时相机中断均为**未标定的启发式压力模型**,不代表具体相机、透明材质或工厂的实测失效分布。
4
+
5
+ index.jsonl 每行记录一个 episode、frame、camera 的 split、场景对、profile、输入文件与真值目标路径。所有路径相对本数据包根目录;深度单位米,camera-z;valid_mask 中 255 有效、0 无效,无效深度必须为 0。短时中断使用同一时间戳的黑色 RGB 和全无效深度,未使用上一帧图像冒充当前帧。
6
+
7
+ 相机中断窗口由种子和相机名确定,跨种子变化以降低时间位置捷径;outage_coverage 逐相机核对实际黑帧和全无效深度。
8
+
9
+ empirical 模式保存客户提供的完整残差拟合profile,只使用train分箱支持范围;范围外或无train支撑的深度无效。sensor_severity 不缩放实测残差,RGB保持原图;来源声明未经独立核验,calibrated仍为false,不能据此声称光学传感器等效。
10
+
11
+ report.json 重新打开文件后统计缺测比例、有效像素深度误差和配对轨迹一致性。缺测率与误差只描述施加的压力,不表示真实传感器精度或模型表现;全缺测帧的深度误差为空。target_dropout_fraction 的分母为目标掩码内正深度像素;目标未可见时为空。
12
+
13
+ sensor_profile/sensor_severity 场景对必须同种子、同 split,逐帧动作、状态、位姿与干净 RGB/深度/掩码一致。只在输入观测中施加变化,可用于深度补全、失效检测、感知鲁棒性评估;策略没有基于受损输入重算动作,不能用既有成功标注宣称闭环控制鲁棒性。
14
+
15
+ 训练时仅使用 train;reference/challenge 必须保持在同一 split。v0.5恢复导出的 observation.state 只含10维本体状态,privileged.simulator_state、supervision.object_pose、干净深度及掩码属于特权监督;部署感知模型的输入应选择 input_rgb、input_depth_observed、input_valid_mask。在独立真实数据上比较基线和增强后的模型,才可以判断迁移收益。
sensors/index.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
sensors/report.json ADDED
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1
+ {
2
+ "summary": {
3
+ "schema_version": "simforge.sensor_report.v1",
4
+ "valid": true,
5
+ "status": "passed",
6
+ "calibrated": false,
7
+ "closed_loop_evaluated": false,
8
+ "real_robot_transfer_validated": false,
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+ "episodes": 24,
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+ "observations": 3360,
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+ "invalid_observations": 0,
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+ "profiles": {
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+ "clean": 12,
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+ "depth_noise": 3,
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+ "target_dropout": 3,
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+ "camera_outage": 3,
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+ "combined": 3
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+ },
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+ "empirical_profiles": [],
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+ "empirical_train_supported_depth_fraction": null,
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+ "empirical_fully_unsupported_observations": 0,
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+ "coverage_warnings": [],
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+ "outage_observations": 66,
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+ "effectively_corrupted_observations": 1293,
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+ "depth_dropout_fraction": 0.02008758060515873,
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+ "target_depth_dropout_fraction": 0.1330217308644278,
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+ "valid_depth_rmse_m": 0.002932024443036638,
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+ "pair_checks": 12,
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training_readiness.json ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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