Add camera sensitivity dataset card (#1)

- Add camera sensitivity dataset card (ea07a63479b9955aa75eb17cd7044e8c21903d7d)

README.md

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+---
+pretty_name: Arena DROID Camera Sensitivity Workflow Sample
+task_categories:
+- robotics
+tags:
+- robotics
+- simulation
+- policy-evaluation
+- sensitivity-analysis
+- isaaclab-arena
+language:
+- en
+size_categories:
+- n<1K
+---
+
+# Arena DROID Camera Sensitivity Workflow Sample
+
+## Dataset Description
+
+Arena-DROID-Camera-Sensitivity-Workflow-Sample is a compact set of episode-level results generated by an Isaac Lab-Arena simulation experiment. It lets users run the documented camera sensitivity analysis without first executing the policy-evaluation sweep.
+
+The experiment evaluates an OpenPI `pi05` policy on a DROID Rubik's-cube pick-and-place task while independently varying the wrist-camera position on three axes. Each JSONL record contains the sampled camera offset, task instruction, episode outcome and length, timestamp, objective progress, and predicate events. The dataset does not contain robot trajectories, actions, observations, images, video, audio, or model weights.
+
+| Dataset version | Records | Successful | Unsuccessful | Data file |
+|---|---:|---:|---:|---|
+| `arena_v0.2_lab_v3.0` | 10 | 7 | 3 | `episode_results_rebuild0.jsonl` |
+
+This is a workflow sample. Its size is sufficient to demonstrate the software path, but not to measure policy robustness or compare policy performance.
+
+## Dataset Owner
+
+- Owner: NVIDIA Corporation
+- Technical contact: [Isaac Lab-Arena maintainers](https://github.com/isaac-sim/IsaacLab-Arena/issues)
+- Hugging Face repository: [nvidia/Arena-DROID-Camera-Sensitivity-Workflow-Sample](https://huggingface.co/datasets/nvidia/Arena-DROID-Camera-Sensitivity-Workflow-Sample)
+
+## Dataset Creation Date
+
+- Simulation run: 2026-08-06
+- Hugging Face repository created: 2026-08-07
+
+## License/Terms of Use
+
+No dataset-specific license is currently declared for this repository.
+
+## Intended Use
+
+The dataset is intended to:
+
+- reproduce the documented Isaac Lab-Arena sensitivity-analysis tutorial without rerunning the evaluation;
+- exercise the episode-results reader and sensitivity-report generation path; and
+- illustrate the episode-result schema produced by a controlled environment-variation sweep.
+
+The dataset is not intended for:
+
+- training or fine-tuning a robot policy;
+- benchmarking, ranking, or comparing policies;
+- drawing conclusions about policy robustness, safety, or real-world performance; or
+- validating a production or safety-critical robotics system.
+
+## Dataset Characterization
+
+### Data Collection Method
+
+The records were generated automatically in simulation. No human teleoperation or manual annotation was used during this evaluation run or included in the released payload. This statement does not describe the separate training data used to develop the OpenPI policy.
+
+The experiment used:
+
+- Isaac Lab-Arena's DROID absolute-joint-position embodiment;
+- an OpenPI `pi05` policy through the Arena OpenPI adapter;
+- the instruction, "Pick up the Rubik's cube and place it in the bowl.";
+- a simulated Rubik's cube, bowl, maple table, and home-office environment;
+- 10 episodes in one simulation environment with seed `42`; and
+- independent wrist-camera translation offsets sampled from `-0.03` m to `0.03` m on each of three axes.
+
+The dataset does not include the simulation assets, OpenPI software, or policy weights used during generation.
+
+### Labeling Method
+
+Isaac Lab-Arena generated the `success`, progress, and event values automatically from the task's objective predicates. There are no human-provided labels.
+
+### Version and Provenance
+
+- Dataset revision: `arena_v0.2_lab_v3.0`
+- Dataset content commit: `6a879e4b09bc9911453dd8271081dfcf7d3aa9e1`
+- Data-file SHA-256: `329a25484c2edc997d74e540b3bfe615a99390270c696c29effb73cc86497ea8`
+- Isaac Lab-Arena introduction: [pull request 1055](https://github.com/isaac-sim/IsaacLab-Arena/pull/1055)
+
+## Dataset Format
+
+The dataset contains one newline-delimited JSON file, `episode_results_rebuild0.jsonl`. Each line is one completed episode.
+
+| Field | Type | Description |
+|---|---|---|
+| `job_name` | string | Experiment run name. |
+| `env_id` | integer | Simulation environment index. |
+| `episode_in_env` | integer | Zero-based episode index within the environment. |
+| `seed` | integer | Experiment seed recorded for the episode. |
+| `success` | boolean | Automatically evaluated task-success outcome. |
+| `episode_length` | integer | Episode length in environment steps. |
+| `language_instruction` | string | Instruction supplied to the policy. |
+| `timestamp` | string | Episode timestamp in ISO 8601-like format. |
+| `variations` | object | Sampled environment-variation values. |
+| `progress` | object | Objective scores, completion state, active predicates, and predicate events. |
+
+The `variations` object contains `droid_abs_joint_pos.camera_extrinsics_wrist_camera`, a three-element floating-point vector in metres. In the camera optical frame:
+
+- element `0` is horizontal displacement: negative is left and positive is right;
+- element `1` is vertical displacement: negative is up and positive is down; and
+- element `2` is depth displacement: negative is backward and positive is forward.
+
+The `progress.events` array records the episode-local environment step, objective, predicate, and score change for each completed task event.
+
+Hugging Face may present the records as an automatically inferred `train` split. That label is a viewer convention; these are evaluation results, not training data.
+
+## Dataset Quantification
+
+- JSONL records: 10
+- Data-file size: 12,101 bytes
+- Successful episodes: 7
+- Unsuccessful episodes: 3
+- Environment IDs: one (`env_id = 0`)
+- Episode indices: 0 through 9
+- Recorded run interval: 2026-08-06 10:43:07 through 10:57:21
+- Images, videos, and audio: none
+
+The released JSONL parses as 10 complete JSON objects. The recorded camera offsets are within the configured `[-0.03, 0.03]` m bounds.
+
+## Personal Data and Third-Party Content
+
+A review of `episode_results_rebuild0.jsonl` at revision `arena_v0.2_lab_v3.0` found no names, email addresses, account identifiers, faces, voices, or real-world sensor captures. The file contains experiment identifiers, fixed task text, numeric results, and timestamps without timezone offsets.
+
+The JSONL contains textual identifiers referring to DROID, OpenPI, and a Rubik's cube. It does not include or redistribute related assets, software, or model weights.
+
+## Limitations
+
+- Ten episodes are too few for reliable sensitivity, robustness, or performance conclusions.
+- All records come from one task, policy variant, seed, and simulation configuration.
+- The dataset contains episode summaries rather than the raw actions, observations, camera frames, or simulator state needed to reproduce individual rollouts.
+- Outcomes depend on the task predicates and thresholds used by the recorded workflow.
+- Simulation results do not establish real-world robot behavior or safety.
+- The timestamps do not include an explicit timezone offset.
+- The JSONL does not identify the exact OpenPI model or software commit used to generate the run.
+- The downloadable sample has a `0.7` success rate. Metrics shown for other runs in the workflow documentation do not describe this file.
+
+## Download and Use
+
+Download the version used by the documented workflow:
+
+```bash
+hf download \
+  nvidia/Arena-DROID-Camera-Sensitivity-Workflow-Sample \
+  episode_results_rebuild0.jsonl \
+  --repo-type dataset \
+  --revision arena_v0.2_lab_v3.0
+```
+
+Follow the [Isaac Lab-Arena sensitivity-analysis workflow](https://isaac-sim.github.io/IsaacLab-Arena/main/pages/example_workflows/sensitivity_analysis/sensitivity_analysis.html) to generate the example posterior report.
+
+## Ethical Considerations
+
+NVIDIA believes Trustworthy AI is a shared responsibility and has established policies and practices to support the development of AI applications. Users should evaluate whether this dataset and the surrounding workflow are appropriate for their use case and should not treat this small simulation sample as evidence of safe or effective deployment.
+
+Please report security vulnerabilities or NVIDIA AI concerns through the [NVIDIA Product Security reporting page](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
+
+## References
+
+- [Dataset repository](https://huggingface.co/datasets/nvidia/Arena-DROID-Camera-Sensitivity-Workflow-Sample)
+- [Pinned dataset revision](https://huggingface.co/datasets/nvidia/Arena-DROID-Camera-Sensitivity-Workflow-Sample/tree/arena_v0.2_lab_v3.0)
+- [Isaac Lab-Arena repository](https://github.com/isaac-sim/IsaacLab-Arena)
+- [OpenPI repository](https://github.com/Physical-Intelligence/openpi)
+- [Sensitivity-analysis workflow source](https://github.com/isaac-sim/IsaacLab-Arena/blob/main/docs/pages/example_workflows/sensitivity_analysis/sensitivity_analysis.rst)
+- [Experiment configuration](https://github.com/isaac-sim/IsaacLab-Arena/blob/main/isaaclab_arena_environments/experiment_configs/droid_pnp_camera_sensitivity_openpi_experiment.yaml)