Accelerate your robotics and spatial computing research with our comprehensive Embodied AI Video Dataset, meticulously engineered to teach intelligent agents how to perceive, reason, and interact within complex environments. This cutting-edge collection provides a holistic training foundation by seamlessly integrating three critical pillars of embodied intelligence data.
The dataset features extensive virtual simulation and digital twin data. This includes physically accurate virtual scenes and precise action trajectories—such as complex grasping poses and diverse multi-scene interaction simulations. This allows your models to learn robustly and safely in scalable digital environments before real-world deployment.
We provide highly valuable real-world multimodal data captured directly by physical robots operating in authentic scenarios. Covering a wide array of both household and industrial tasks, these sequences deliver synchronized streams of visual inputs, force sensing (haptics), and precise physical action trajectories, effectively bridging the crucial sim-to-real gap.
The collection captures the nuanced dynamics of human-robot collaboration. By incorporating rich interaction data—including direct human operation demonstrations, operational commands, and real-time behavioral feedback during cooperative tasks—this dataset empowers AI models to accurately understand human intent. Whether you are developing advanced industrial automation or intuitive next-generation household robotics, this multi-tiered dataset offers the essential groundwork for your Embodied AI breakthroughs.
| Item | Details |
|---|---|
| Data Type | Embodied AI Video & Multimodal Dataset |
| Total Duration | 20,000 hours |
| File Format | MP4 |
| Data Sources Included | Virtual simulation and digital twin data (e.g., grasping poses, interaction simulations)Real-world physical robot captures (e.g., visual, haptic, and action trajectories)Human-robot collaboration data (e.g., operation demonstrations, commands, and feedback) |
