robotics-vla
Expert guidance for Vision-Language-Action (VLA) robot foundation models — covering architecture design, training pipelines, data strategy, deployment, and evaluation. Use when (1) designing or implementing a generalist robot policy (VLA model), (2) setting up pre-training or fine-tuning pipelines for robot manipulation, (3) choosing action representations (flow matching vs. diffusion vs. autoregressive), (4) structuring multi-embodiment robot datasets, (5) evaluating dexterous manipulation tasks, (6) implementing action chunking or high-level policy decomposition. Based on the pi0 architecture (Physical Intelligence, 2024).
Installation and usage
Expert guidance for Vision-Language-Action (VLA) robot foundation models — covering architecture design, training pipelines, data strategy, deployment, and evaluation. Use when (1) designing or implementing a generalist robot policy (VLA model), (2) setting up pre-training or fine-tuning pipelines for robot manipulation, (3) choosing action representations (flow matching vs. diffusion vs. autoregressive), (4) structuring multi-embodiment robot datasets, (5) evaluating dexterous manipulation tasks, (6) implementing action chunking or high-level policy decomposition. Based on the pi0 architecture (Physical Intelligence, 2024).
Once installed, you can use this skill by running the following command in your terminal:
skills use robotics-vla