[{"@type":"PropertyValue","name":"Calibration info","value":"JSON format"},{"@type":"PropertyValue","name":"Raw RGB camera video","value":"MP4 format, H.264 compression"},{"@type":"PropertyValue","name":"Raw infrared fisheye camera data","value":"MJPG format"},{"@type":"PropertyValue","name":"SLAM trajectory log","value":"JSON format"},{"@type":"PropertyValue","name":"Raw sensor data records","value":"HDF5 format"},{"@type":"PropertyValue","name":"Depth data","value":"MKV format"},{"@type":"PropertyValue","name":"Demo video of 3D gesture mapped to 2D image","value":"MP4 format"},{"@type":"PropertyValue","name":"Reconstructed point cloud","value":"PLY format"},{"@type":"PropertyValue","name":"Annotation info","value":"JSON format"}]
{"id":2264,"datatype":"1","titleimg":"https://www.nexdata.ai/shujutang/static/image/index/datatang_tuxiang_default.webp","type1":"282","type1str":null,"type2":"283","type2str":null,"dataname":"10000-Hours 6-Camera Ego Embodied AI Dataset","datazy":[{"title":"Calibration info","content":"JSON format"},{"title":"Raw RGB camera video","content":"MP4 format, H.264 compression"},{"title":"Raw infrared fisheye camera data","content":"MJPG format"},{"title":"SLAM trajectory log","content":"JSON format"},{"title":"Raw sensor data records","content":"HDF5 format"},{"title":"Depth data","content":"MKV format"},{"title":"Demo video of 3D gesture mapped to 2D image","content":"MP4 format"},{"title":"Reconstructed point cloud","content":"PLY format"},{"title":"Annotation info","content":"JSON format"}],"datatag":"ego centric,Embodied AI,Physical AI","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":null,"samplePresentation":[],"officialSummary":"A multimodal embodied AI dataset totaling 10,000 valid hours, collected with a six-camera Ego head-mounted device, and subjected to multiple rounds of quality inspection, AI preprocessing, and fine-grained manual action segmentation and annotation. It covers 25 categories of real-world business scenarios and outputs multi-sensor data in MCAP format along with task-action labels in multiple languages including Chinese, English, Japanese, and Korean.","dataexampl":null,"datakeyword":["ego centric","embodied AI dataset","Nexdata","off-the-shelf datasets"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Type","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"embodiedAi","dataShowType":"[{\"code\":\"0\",\"language\":\"ZH\"},{\"code\":\"1\",\"language\":\"ZH\"},{\"code\":\"2\",\"language\":\"EN\"},{\"code\":\"3\",\"language\":\"EN\"}]","productNameEn":"10000-Hours 6-Camera Ego Embodied AI Dataset","BGimg":"","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"]}
A multimodal embodied AI dataset totaling 10,000 valid hours, collected with a six-camera Ego head-mounted device, and subjected to multiple rounds of quality inspection, AI preprocessing, and fine-grained manual action segmentation and annotation. It covers 25 categories of real-world business scenarios and outputs multi-sensor data in MCAP format along with task-action labels in multiple languages including Chinese, English, Japanese, and Korean.
This is a paid dataset licensed for commercial use. Ready-made datasets are available for immediate integration into AI projects.
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
Recommended Dataset
