Records
6
HF AUTHOR CLUSTER
6 robotics-tagged HF records from cadene, totaling 659,048 cumulative downloads. Some records cite published arxiv research.
DIRECT ANSWER
Author clusters consolidate every record from one publisher into a single buyer-review surface. cadene ships 6 robotics datasets on Hugging Face. Top license: apache-2.0. Of those, 6 get a full standalone page, 0 get a shorter profile, and 0 are folded into this cluster.
6
659,048
apache-2.0
DATASETS
6 of 6 datasets
Published Feb 2025 · apache-2.0 · cadene
This dataset was created using LeRobot. DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset One of the biggest open-source dataset for robotics with 27.044,326 frames, 92,223 episodes, 31,308 unique task description in natural…
Published Mar 2025 · apache-2.0 · cadene
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "Franka", "total_episodes": 95600, "total_frames": 27612581, "total_tasks": 0, "total_videos": 286800, "total_chunks":…
Published Apr 2025 · apache-2.0 · cadene
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "robot_type": "Franka", "total_episodes": 95584, "total_frames": 27607757, "total_tasks": 49596, "chunks_size": 1000,…
Published May 2025 · apache-2.0 · cadene
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "robot_type": "AgiBot_A2D", "total_episodes": 28122, "total_frames": 47613574, "total_tasks": 30, "chunks_size": 1000,…
Published Aug 2024 · not specified · cadene
This dataset was created using 🤗 LeRobot.
Published May 2025 · apache-2.0 · cadene
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "robot_type": "Franka", "total_episodes": 95584, "total_frames": 27607757, "total_tasks": 49596, "chunks_size": 1000,…
KEEP DIGGING
A dataset record is only useful when it connects into the rest of the buyer workflow. The next review step is usually not another summary; it is a fit check, rights triage, source comparison, or custom bounty spec that names the missing proof.
For physical AI teams, the hard question is whether the public source can support a specific model objective under real deployment constraints. That requires adjacent dataset records, tools, comparisons, and sourcing paths, plus external references that a reviewer can open and challenge.
Use the links below to keep the review grounded. Start broad when discovery is incomplete, move into profile and comparison pages when the candidate source is known, and switch to custom collection when the blocker is rights, consent, geography, robot embodiment, or target environment coverage.
TRUELABEL ROUTING
If the Hub records don't carry the license, consent, or deployment fit your team needs, commission a custom collection on the same modality with explicit commercial terms.