--- library_name: opentau tags: - robotics - vla - pi05 - robocasa - manipulation - flow-matching - pytorch base_model: williamyue/pi05_base license: apache-2.0 datasets: - robocasa/CloseMicrowave - robocasa/CloseFridge - robocasa/CloseCabinet repo_url: https://github.com/TensorAuto/OpenTau --- # Robocasa_navigatekitchen A **pi0.5 (π₀.₅)** Vision-Language-Action (VLA) model, finetuned on the **ROBOCASA** robotic manipulation/navigation benchmark using the **OpenTau** training framework. This model is designed to follow natural language instructions to perform manipulation/navigation tasks in a simulated kitchen environment. **For full documentation, evaluation results, and inference code, please visit the repository:**
👉 **[https://github.com/TensorAuto/OpenTau](https://github.com/TensorAuto/OpenTau)** --- ## Model Details ### Description - **Model Type:** Vision-Language-Action (VLA) Model - **Base Architecture:** π₀.₅ (pi0.5) by Physical Intelligence - **Backbone:** PaliGemma-3B (VLM) + Gemma-300M (Action Expert) - **Training Data:** Robocasa Benchmark - **Framework:** OpenTau ### Architecture The pi0.5 architecture uses a flow-matching-based policy designed for open-world generalization. It combines a Visual Language Model (VLM) for high-level semantic understanding with a smaller "action expert" model that generates continuous joint trajectories (10-step action chunks) via flow matching. --- ## Training and Evaluation ### Dataset This model was finetuned on the **Robocasa** benchmark dataset. The Robocasa suite consists of human-teleoperated and mimicgen demonstrations for manipulation and navigation, covering: - **CloseMicrowave** (Atomic) - **CloseFridge** (Atomic) - **CloseCabinet** (Atomic) ### Results Training on 100 Human demonstrations, our model achieves **98% , 80% and 65%** success rate on CloseMicrowave, Close Fridge and Close Cabinet tasks respectively. For detailed usage instructions, success rates, baseline comparisons, and evaluation protocols, please refer to the [OpenTau GitHub Repository](https://github.com/TensorAuto/OpenTau).