Lerobot Community Datasets v3 A Cross Embodiment Pretraining Dataset for Vision Language Action Models A large scale robotics dataset for vision language action learning, featuring 791 datasets across 46 robot types , enabling cross embodiment pretraining for generalist robot policies. Overview This is a crowdsourced, open source dataset compiled from 235 community contributors worldwide. Building upon the pretraining datasets used for SmolVLA, Community Datasets v1 and v2, this cleaned and organized version opens the door for cross embodiment training on another completely new batch of community contributed data. The dataset spans 46+ robot embodiments including single arm, bimanual, mobile manipulation, and a few humanoid robots. All data was collected using the LeRobot framework and is compatible with the VLAb pretraining framework. 📊 Dataset Statistics Metric Value Total Datasets 791 Total Episodes 50,622 Total Frames 25,971,082 Total Duration 251.5 hours (10.5 days) Contributors 235 Robot Types 46 different embodiments Action Dimensions 12 different configurations Average Hours/Dataset 0.30 🤖 Robot Type Distribution By Category Single arm manipulators : 88.4% (699 datasets)…
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