2 个仓库
Processes robotic observations and actions into a consistent format for multimodal training.
Distinct from Multi-Modal Training: Focuses on the data formatting of robotic trajectories rather than the overall multi-modal training pipeline
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OpenVLA is a vision-language-action model and framework designed for general-purpose robotic manipulation. It provides a robotic policy training framework and a control inference engine that map visual and textual inputs to robotic control actions, enabling zero-shot instruction following on hardware. The project includes a robotics dataset pipeline for standardizing diverse trajectory data and managing dataset mixtures. It supports large-scale model training through distributed GPU compute and sharded data parallelism, alongside parameter-efficient adaptation for fine-tuning models to new ta
Provides a pipeline for standardizing diverse robotic trajectory data into a consistent format for training.
AgiBot-World is a suite of software pipelines and tools designed for robotic policy training, dataset standardization, embodiment transfer, and performance benchmarking. It provides infrastructure for developing bimanual manipulation policies using foundation models and human-reference trajectory data. The project features a robot embodiment transfer suite that adapts pre-trained models to different robot bodies without requiring new multi-embodiment training data. It also includes a specialized evaluation framework for validating vision-language-action models through open-loop testing and ph
Implements a unified data format that normalizes diverse robotic sensor streams and actions for consistent training.