Wetour Robotics发布Orchestra肌电与第一视角视觉机器人学习系统开发演示

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AUSTIN, Texas - Wetour Robotics Limited (NASDAQ:WETO) released a development demonstration of Orchestra, a system combining surface electromyography with first-person vision to capture human hand data for robot learning, according to a press release statement.
The system pairs Conductor, an 8-channel sEMG wristband that measures muscle activity, with VisionLink, a first-person camera. The dual-modal approach is designed to address limitations in vision-only capture systems, which cannot measure force application and lose hand tracking when objects obstruct the camera view.
In an internal carrying task, the vision-only pipeline failed to locate the hand in 21.8% of frames, including a continuous dropout lasting 4.32 seconds. The architecture uses sEMG signals during visual gaps, though the cross-modal correction strategy remains in validation.
The demonstration shows an on-device model that outputs 20 joint angles from sEMG data. In internal benchmarking, processing a one-second sEMG window required 50.4 milliseconds with zero lookahead, representing model processing time rather than complete system latency.
The force-estimation pipeline converts sEMG signals into kilogram-equivalent grasp-force estimates using scale-based calibration. The pipeline has been validated on synthetic data, while validation with live wristband recordings remains under development.
The demonstration includes five tasks: packing a lunch box, sorting pills, disassembling a pen, measuring a drone with calipers, and installing a drone propeller.
"A camera can show where a hand moved, but not how hard it worked, and it can go blind at the exact moment contact happens," said Nan Zheng, Chief Executive Officer.
The system is being developed to structure demonstrations for robot training by layering events such as reach, grasp, hold and release over continuous hand motion.
Wetour Robotics is a Physical AI infrastructure and wearable robotics company headquartered in Austin, Texas.
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