Initial dataset upload

.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+episodes/s2e_v2_20260115_224153/planner_candidates.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: mit
+task_categories:
+  - robotics
+  - other
+tags:
+  - vision-language-model
+  - navigation
+  - sidewalk
+  - autonomous-vehicles
+  - trajectory-selection
+  - latency
+size_categories:
+  - n<1K
+pretty_name: AgenticNav (mini split)
+---
+
+# AgenticNav — mini split
+
+Mini fixture for [AgenticNav](https://github.com/pengzhenghao/AgenticNavigation), the dataset accompanying the paper *"Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation"*.
+
+This split contains **1 episode** (`s2e_v2_20260115_224153`) with **3 takeover clips** for fast CI / quickstart smoke tests. For full evaluation, use the [`agenticnav-hard`](https://huggingface.co/datasets/pengzhenghao97/agenticnav-hard) split.
+
+## Quickstart
+
+```bash
+git clone https://github.com/pengzhenghao/AgenticNavigation
+cd AgenticNavigation
+uv sync && source .venv/bin/activate
+python scripts/download_dataset.py --split mini   # writes data/agenticnav-mini/
+python -m agentnav.cli.trajectory_selection \
+    --dataset data/agenticnav-mini --model dummy_argmax --write-report
+```
+
+## Layout (canonical episode schema v0.1.0)
+
+```
+agenticnav-mini/
+├── dataset_manifest.json
+├── episodes/
+│   └── s2e_v2_20260115_224153/
+│       ├── episode.json
+│       ├── rgb.jsonl                  # video-backed RGB stream (5 Hz)
+│       ├── odom.jsonl                 # robot pose in map ENU frame
+│       ├── planner_candidates.jsonl   # S2E candidate trajectories + scores per tick
+│       └── assets/rgb/
+│           ├── front.mp4              # canonical RGB video
+│           ├── front_pinhole.mp4      # pinhole-projected RGB (for planner input)
+│           └── sample_*.png           # individual frames referenced by takeover_clips
+└── takeover_clips/
+    ├── takeover_clips.jsonl           # 3 clips
+    └── summary.json
+```
+
+See the [code repo](https://github.com/pengzhenghao/AgenticNavigation) for the full schema (`src/agentnav/schema/canonical_episode.py`).
+
+## License
+
+MIT. See `LICENSE` in the [code repo](https://github.com/pengzhenghao/AgenticNavigation).
+
+## Citation
+
+```bibtex
+@inproceedings{peng2026slowbrain,
+  title={Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation},
+  author={Peng, Zhenghao and others},
+  booktitle={TODO},
+  year={2026}
+}
+```

dataset_manifest.json

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+{
+  "dataset_name": "agenticnav-mini",
+  "dataset_version": "0.1.0",
+  "schema_version": "0.1.0",
+  "episodes": [
+    "s2e_v2_20260115_224153"
+  ],
+  "description": "Mini split (1 episode + 3 takeover clips) of AgenticNav for CI / quickstart."
+}

episodes/s2e_v2_20260115_224153/assets/rgb/front.mp4

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+oid sha256:2dd03734fde880bed5be91fc3756865ffaae8d73c1d9d491e60c44aa5f4deb08
+size 34491144

episodes/s2e_v2_20260115_224153/assets/rgb/front_pinhole.mp4

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episodes/s2e_v2_20260115_224153/episode.json

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+{
+  "episode_id": "s2e_v2_20260115_224153",
+  "quality": {
+    "missing_streams": [
+      "gps",
+      "route",
+      "control"
+    ],
+    "notes": "Converted from s2e_v2 folder example_data; timestamps are sample_index * dt_s. If sample_<i>_pose.npy is present, we write canonical odom.jsonl and GT metrics use executed future odom transformed into robot local frame."
+  },
+  "schema_version": "0.1.0",
+  "stats": {
+    "auto_enabled_false": 515,
+    "auto_enabled_ratio": 0.0,
+    "auto_enabled_true": 0,
+    "distance_auto_m": 0.0,
+    "distance_human_m": 147.68982672910582,
+    "distance_m": 147.68982672910582,
+    "planner_candidates_total": 515,
+    "takeover_events": 1,
+    "time_auto_s": 0.0,
+    "time_human_s": 103.00000000000092
+  },
+  "streams": {
+    "odom": {
+      "records_ref": "odom.jsonl"
+    },
+    "planner_candidates": {
+      "records_ref": "planner_candidates.jsonl"
+    },
+    "rgb": {
+      "records_ref": "rgb.jsonl"
+    }
+  }
+}

episodes/s2e_v2_20260115_224153/odom.jsonl

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