Turning the Real World into the Data Infra for Embodied AI

A wrist-worn first-person capture terminal for embodied AI algorithm teams, humanoid robotics R&D, and industrial line digitalization — worn on the hand to capture the full manipulation process, outputting microsecond-synchronized multimodal raw data for world-model training, human-to-robot motion transfer, and digitized SOP capture on production lines.

A humanoid-gripper-shaped teleoperation capture handle with an integrated tri-camera and trigger mechanism, synchronously recording the force and pose trajectories of the entire grasp-pinch-release process — compatible with calibration and real-robot data capture across multiple end-effector types.

Application scenarios span humanoid robot head perception, large-scale multimodal world-model dataset production, industrial digital-twin scenarios, remote human-robot teaching, robot motion transfer, commercial VIO/SLAM positioning system R&D, and training data capture for large embodied AI models.

As soon as capture is complete, clarity, exposure, frame-drop rate, and multi-channel sync are checked locally, giving an instant PASS / WARN / FAIL result; during capture, body/hand pose skeletons are shown in real time to confirm framing, motion completeness, and keypoint stability — substandard data is re-recorded on the spot.

Once uploaded data passes validation, unpacking, time alignment, standardization, and high-precision solving are completed automatically — human involvement is limited to QC, annotation, and evaluation steps that require expert judgment.

Supports unified connection, preview, recording, and packaging for multiple sensor streams — four RGB channels, two IR channels, IMU, and more — with a shared session clock guaranteeing data synchronization.

Chunked upload, resumable transfer, hash integrity checks, and idempotent duplicate-upload handling make results verifiable and failures recoverable; a unified identifier establishes complete data lineage, traceable to the project, capture task, raw capture package, solving task, and the operator and timestamp at every stage.

Motion SOPs, target quantities, quality requirements, and acceptance thresholds are all defined before a task is dispatched, turning capture from a personal-experience-dependent process into standardized execution — suited for scaled production across many operators, devices, and sites.