Provision of infrastructure services from end-to-end to end-to-end data sets for human robot manufacturers and large models
4.3 million + operational tracks collected · Service multiple head-shaped robots. Animal
Smart model training is extremely demanding in terms of size and quality of data, and traditional data collection methods are difficult to meet VLA model landing needs
The limited size of the open data set and the single scene did not meet the demand for mass, high-quality physical data for VLA model training, and the long-term low success rate of real-world missions Fancy。
High input from self-building teams, difficult personnel management, uneven quality of collection, difficulty in replicating and high cost of equipment acquisition and maintenance。
The cost per item is up to a thousand dollars per person, it cannot be scaled up, the length of the period is seriously affecting the iterative rhythm of the model and the project budget cannot afford。
The simulation environment training strategy is significantly degraded when it migrates to a real robot, lacking a data-similar-training closed-ring validation mechanism, with less impact than expected。
Base capacity matrix from hardware equipment, capture platform to AI-marked end to end-to-end body data
370g light Quantification Design, 6-hour camera, suitable for long operation for collection
8K binoculars + force perception + eye movement + body motion, professional multi-modular data collection
Free of charge, open to SDK, quick start to assist academic research
Finger-tip sensory perception, hand-to-hand cover, complete touch information.
38g super light, full hand operating perspective, fine operating data collection
3500+ devices managed online in real time, fully processable and functional
87% to 200 yuan/bar, AI premark + manual review 6-8 times faster
Retail/hotel/logistics/medical/industry/household coverage
NVIDIA Omniverse authentication, closed loop verification of migration effects
| Parameter Item | Specifications |
|---|---|
| 设备型号 | E6（轻量）/E8（专业）/E2（科研） |
| 相机配置 | 6-way fast door RGB / 8K binary + multimodular |
| 重量 | 370g（E6）/ 850g（E8）/ 420g（E2） |
| Battery Life | 8小时连续采集 |
| Time Sync | <500ns 硬件时钟 |
| 平台管理 | 3500+台设备实时在线 |
| 标注效率 | AI premark + manual review, 6-8 times speed |
| 数据集规模 | 430万+条轨迹，6大行业 |
| 生态兼容 | NVIDIA Omniverse / 华为昇腾 / ROS2 |
The real mission success rate of a head unicorn VLA model increased from 43 per cent to 89 per cent, significantly reducing the training cycle。
Senior technicians digitized, with new technicians increasing from 93 per cent to 98.7 per cent and skills transfer more efficiently Increase。
TB-Retail-100K with 100,000 barometer tracks to accelerate the deployment of retail service robots。
TB-Hotel-50K with 50,000 room service tracks to support hotel service robot training。
Basic operations such as abdominal surgery to provide quality training data for medically assisted robots。
TB-Home-150K with 150,000 daily family trajectories to support the home service landscape Land。
"Lang Hui's personal data acquisition capability has been supplemented by short panels at critical stages of our VLA model training.
"Senior Technician Operating Data collected by E8 Equipment increased the pass rate of new Technicians from 93% to 98.7%."
"E2 scientific equipment has reduced our preparation time from 15 minutes to 30 seconds."
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