Data Acquisition Facility_Robotics-SHANGHAI CHINGMU VISION TECHNOLOGY CO., LTD

Business pain points

Simulated data often lacks real-world validation, leading to inconsistent data quality

Single-modality data limits a robot’s ability to learn complex skills and generalize

Self-built data pipelines are inefficient, complex, and costly to maintain

Platform-specific data lacks universality, making cross-platform scaling difficult

Manual annotation and quality control make large-scale data production hard to standardize

Our advantages

High-quality source data generated from precise real-world motion capture

Synchronized capture of humans, robots, objects, and environments with spatio-temporal alignment

Scalable and cost-effective third-party data services tailored to specific needs

Standardized training data designed for transfer across diverse robot platforms

End-to-end services from scene design and acquisition to annotation and quality inspection

Introduction

High-quality ground truth data is essential for embodied AI to move toward generalization. CHINGMU Data Acquisition Facility uses optical motion capture to collect real-world multimodal data from humans, robots, objects, and environments, generating strongly spatio-temporally aligned datasets.

From scene design and data capture to annotation and quality control, CHINGMU provides an end-to-end data production pipeline for robot perception, decision-making, control algorithms, skill learning, and fine manipulation.

Applications: Humanoid Robots · Skill Learning · Algorithm Training · Fine Manipulation · Robot eva1uation

Build high-quality real-world datasets for the next generation of embodied intelligence.

Data acquisition

Product components

Pulse Series Optical Mocap Camera

Built for desktop and small-scale spaces; high precision, multimodal, rapid deployment

Project Decode

Multimodal embodied AI data acquisition for building high-fidelity, reusable datasets efficiently

OptiUMI

Lightweight wearable gripper capturing verifiable, trainable, transferable manipulation data in real environments

Pulse Series Optical-Inertial Fusion Gloves

Sub-millimeter multimodal hand motion capture

3D Vivid Memory

Scans bodies, objects, and environments into high-precision digital models

Embodied DataHub

Data management platform for efficient dataset construction and multi-task reuse

Advantages of the plan

Multimodal Data AcquisitionCaptures and correlates motion, vision, control signals, tactile feedback, object states, and environmental information to form high-quality behavior-state-visual datasets that improve model understanding and generalization.

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High-Precision Ground TruthResolves the 6DoF pose and motion trajectory of robot bodies, joints, and end-effectors in real time with sub-millimeter accuracy. This provides reliable ground truth labels and validation benchmarks for kinematic modeling, sensor calibration, SLAM, controller optimization, and algorithm eva1uation.

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Full-Process Service CoverageProvides full-chain services from equipment selection and deployment to acquisition procedure design, raw data processing, annotation, and quality inspection. Customers can obtain out-of-the-box data production capability without coordinating multiple vendors or building complex pipelines from scratch.

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Verification & OptimizationBy comparing algorithm outputs such as vision-based pose estimation with motion capture ground truth, system errors can be accurately quantified, optimization directions can be clearly identified, and a complete data-driven R&D loop can be established: acquire, train, verify, and optimize.

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Cross-Platform TransferStandardized data formats support seamless migration across different robot brands, body structures, and control systems, enabling rapid cross-platform validation and reducing the cost of repeated data collection.

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System Flexibility and ScalabilityThe system can transmit data via VRPN, TrackD, DTrack, and LiveStream, and provides a rich set of SDK plugins for data exchange with various platforms. It supports secondary development and runs on Windows, Mac, Linux, Android, Kylin, and other operating systems. It supports development platforms such as PX4, ROS/ROS2, and Raspberry Pi, and interfaces with C++, Python, MATLAB, Simulink, LabVIEW, and other programming languages.

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