As robot learning scales from controlled lab settings to real‑world environments, one bottleneck keeps appearing: data collection.
Teleoperation is precise but slow. Third‑person cameras miss the operator’s viewpoint. Consumer action cameras lack the sensor synchronization that modern imitation learning and VIO pipelines require.
A new hardware option is entering the space. Our Ego Camera is a head‑worn binocular stereo camera built specifically for egocentric data capture in embodied AI and robot manipulation research.
A Viewpoint That Matches the Robot
The module is worn on the human head — like a lightweight headband — and records exactly what the operator sees during a task. This first‑person (egocentric) perspective has become a key focus in recent robotics research.
Large‑scale studies from 2025 to 2026 — including HumanEgo, EgoMimic, and EgoScale — have shown that robot policies trained on human egocentric video can match or outperform those trained on teleoperation data, at a fraction of the collection cost. The perspective matters: the robot, when deployed, sees the world from its own onboard sensors, not from a ceiling or tripod mount.
Our Ego Camera is designed to bridge that gap, providing training data that matches the robot’s actual inference viewpoint, eliminating perspective mismatch for model training.
Sensor Design for Research Pipelines
Global-Shutter Stereo Sensors
The camera module uses two global‑shutter 2MP sensors with a 60–65° horizontal field of view, consistent with the standard FOV of humanoid robot head vision modules. Global shutter is a deliberate core design choice: every pixel exposes simultaneously, fully eliminating rolling‑shutter jelly distortion that corrupts fast hand and body movements during dynamic recording.
Raw Data Preservation (No EIS)
We intentionally remove onboard EIS electronic image stabilization. EIS crops the original field of view and modifies factory-calibrated intrinsic & extrinsic parameters, which would break stereo matching and camera-IMU calibration consistency. Raw full-frame original data is reserved for backend robot algorithm processing.
Microsecond Hardware Synchronization
Built-in ICM-2688 6‑axis IMU (accelerometer + gyroscope, sampling at 200–500 Hz) is synchronized via dedicated GPIO trigger signal. A unified pulse signal sent through GPIO pins triggers stereo cameras and IMU sampling simultaneously. The sync error is under 10 microseconds, and every video frame and IMU sample carries a unified hardware timestamp.
This level of synchronization is a mandatory standard for mainstream VIO pipelines like VINS‑Fusion and OpenVINS, where software‑only timestamp alignment accumulates obvious trajectory drift over long recording sequences.
Onboard Calibration Storage
Full factory calibration covers stereo intrinsics, extrinsics, and camera‑to‑IMU transforms. All calibration parameters are stored in onboard Flash and fully readable through the cross-platform SDK — no on-site re-calibration required after equipment startup.
Deployment Flexibility
Two operational modes are supported to cover all research scenarios.
Standard Multi-Format Data Output
1. Onboard TF card local recording (offline capture)
- Synchronized left & right binocular MP4 video files for quick visual preview
- Independent CSV logs storing IMU raw data paired with microsecond timestamps
2. Host PC recording via SDK (USB connection under ROS/ROS2 environment)
Supports exporting complete synchronized ROSbag and lightweight MCAP sensor datasets, fully compatible with mainstream robotics development ecosystems.
All hardware timestamps are embedded for each frame and IMU sample. Complete factory calibration parameter files are accessible through the official SDK.
Notably, the module carries no onboard AI processing or auto‑annotation functions. Its core positioning is outputting clean, time-aligned raw sensor data, leaving model training, target detection and algorithm inference to researchers’ independent development pipelines.
Customization & Commercial Availability
The Ego Camera is now available for global research laboratories, robotics startups and humanoid robot manufacturers. Customizable stereo baseline distance and lens FOV configurations are supported for bulk ODM volume projects.
Full technical SDK, operation documentation and sample test codes are provided for every order to lower hardware integration costs.
Get In Touch
If you need product samples, SDK documentation, technical parameter consultation or customized hardware solutions for your robot learning project, please send an inquiry via email. Our engineering team offers one-on-one technical support for SLAM, VIO and embodied AI dataset collection projects.
Post time: Jul-29-2026
