SSRobotics · Source Code Collection
Part of Humanoid Robot Hub · 🔎 Search all resources
Robotics dataset catalogs, data formats and training data utilities.
คลัง Dataset หุ่นยนต์ รูปแบบข้อมูล และเครื่องมือจัดเตรียมข้อมูลฝึก
Curated by SSRobotic — Robotics Engineer & Open-source Curator. This repository is a focused resource directory and engineering guide. Linked SDKs, models and research implementations belong to their original creators.
| Resource | What it provides | Keywords | Original source |
|---|---|---|---|
| LeRobot | Robot learning tools, datasets and policies. A supporting embodied AI resource; hardware support is project-specific. | Imitation learning, Datasets, Python | huggingface |
| X-Humanoid Training Toolchain | Tools connecting TienKung / RoboMIND workflows with LeRobot. | TienKung, RoboMIND, LeRobot | Open-X-Humanoid |
| Open X-Embodiment | Cross-embodiment robot dataset resources and supporting tooling. | Datasets, Cross-embodiment, Robotics | google-deepmind |
| RoboMIND Dataset | Multi-embodiment demonstration data, including TienKung. See the dataset card for access conditions. | RoboMIND, Demonstrations, TienKung | X-Humanoid / RoboMIND |
| ArtVIP Assets | Articulated-object digital-twin datasets and scene assets from X-Humanoid. | Digital twin, USD, Assets | X-Humanoid |
12 tracked upstream files — เปิดโฟลเดอร์ด้านล่างเพื่อดูโค้ดจริง โมเดล และตัวอย่างต้นฉบับ
| Project files | Files | Pinned source | License / notices |
|---|---|---|---|
| google-deepmind/open_x_embodiment | 12 | 9eeb68b989ef |
LICENSE |
Source manifest records commits, file counts, Git LFS pointers and external submodules. Per-file manifests record original Git blob hashes. projects/ keeps upstream code, README files, licenses and notices; SSRobotics supplies the organization and guides.
git clone --depth 1 https://github.com/SSRobotic/humanoid-datasets.git
cd humanoid-datasetsThe Open X-Embodiment folder contains real dataset inspection/loading notebooks and documentation. Raw robot datasets are downloaded separately from the original providers; each dataset retains its own access conditions and license.
- Select a dataset that matches the embodiment, task and sensing setup.
- Review its access conditions, license, formats and train / evaluation split.
- Inspect a small documented example and preserve task / frame metadata during conversion.
Read the engineering guide for a practical selection checklist. resources.json contains the structured entries.
🌐 Browse all 14 categories
🦾 Models & URDF · 🌐 Simulation · 🧠 Robot Learning · ⚙️ Whole-body Control · 👁️ Vision & 3D Perception · 🤏 Manipulation & Planning · 🎮 Teleoperation · 💾 Datasets & Demonstrations · 💬 Vision-Language-Action · 🔌 Hardware & SDKs · 📡 ROS & Integration · 📚 Research & Benchmarks · 🟢 Isaac Sim & Isaac Lab · 🧮 Robotics Algorithms
⭐ Star the Hub · 👤 Follow SSRobotic · 💡 Suggest a resource
Contribute accurate descriptions and original source links through the Hub contribution guide. Source terms, model compatibility and dataset access conditions remain with each upstream project.