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1,042 Segments 6-camera Egocentric Embodied AI Dataset
embodied ai dataset
robot learning dataset
robotics training data
egocentric dataset
robot perception dataset
multimodal robotics dataset
SLAM dataset
This dataset contains 1,042 egocentric video segments (approximately 35 seconds each) collected across 34 locations and 6 real-world environments, including homes, offices, and retail scenarios. Powered by self-developed VSLAM system, achieving millimeter-level positioning, multi-sensor hard-triggered synchronization (≤1ms), and a high frame rate of 60fps for RGB. It includes multi-view videos, calibrations, point clouds, SLAM trajectories, and gesture recognition results in standard formats. Designed for embodied AI, spatial perception, and 3D reconstruction, it offers high precision, diverse scenarios, and out-of-the-box usability, making it ideal for training robust perception-action models.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data Content
1042 segments of multi-scenario ego-centric collected data, each approximately 35 seconds long with complete actions. Each segment includes: 6-camera video, relevant parameters, reconstructed point cloud, SLAM post-processed trajectory, and a video showing gesture keypoint recognition results.
Data Distribution
Home scenes: 293 segments; Office scenes: 217 segments; Home renovation scenes: 52 segments; Retail scenes: 299 segments; School scenes: 114 segments; Warehouse scenes: 49 segments.
Data Quality
RGB camera resolution: 1600x1200, frame rate: 60 fps; Monochrome fisheye cameras: 640x480, frame rate: 30 fps. Cameras are hardware-triggered for synchronous exposure.
What types of Embodied AI applications can Nexdata’s datasets support?
Nexdata’s Embodied AI datasets are designed to support a wide range of robotics and embodied intelligence applications, including robot perception, manipulation, navigation, human-robot interaction, and Vision-Language-Action (VLA) model development. Depending on the dataset, data may include multimodal video, sensor data, robot trajectories, actions, poses, and other annotations for training and evaluation.
Can Nexdata customize Embodied AI datasets based on our specific requirements?
Yes. If our off-the-shelf datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target robot platform, tasks, environments, sensors, data volume, annotation requirements, and model specifications, helping you build datasets tailored to your specific Embodied AI or VLA project.
Can Nexdata support large-scale Embodied AI data collection projects?
Yes. Nexdata operates an 8,000-square-meter real-world data collection dojo that enables large-scale and diverse data collection for robotics and Embodied AI applications. The facility can support customized environments, task scenarios, robot operations, and multimodal data collection, allowing us to accommodate projects with complex requirements and large data volumes.
Specifications
Sample
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