Wetour Robotics发布sEMG与第一视角视觉融合的Orchestra开发演示

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6-K
1
ea0304689-6k_wetour.htm
REPORT OF FOREIGN PRIVATE ISSUER
UNITED STATES
SECURITIES AND EXCHANGE COMMISSION
WASHINGTON, D.C. 20549
FORM 6-K
REPORT OF FOREIGN PRIVATE ISSUER
PURSUANT TO RULE 13a-16 OR 15d-16 UNDER
THE SECURITIES EXCHANGE ACT OF 1934
For the month of September 2026
Commission File Number: 001-42536
Wetour Robotics Limited
(Translation of registrant’s name into English)
Room 7003
3300 N Interstate 35 Ste 700
Austin, TX 78705
(Address of principal executive offices)
Indicate by check mark whether the registrant
files or will file annual reports under cover of Form 20-F or Form 40-F.
Form 20-F ☒ Form
40-F ☐
Incorporation
by Reference
This report
on Form 6-K (the “Report”) shall be deemed to be incorporated by reference into the registration statements on
Form
S-8
(File No. 333-291960 and Form F-3 (File Nos.
333-294373
and
333-295457
) of the Company,
including any prospectuses forming a part of such registration statements, and to be a part thereof from the date on which this Report
is filed with the U.S. Securities and Exchange Commission (the “SEC”), to the extent not superseded by documents or reports
subsequently filed or furnished.
EXHIBITS
Exhibit No.
Description
99.1
Press Release dated September 1, 2026
1
SIGNATURES
Pursuant to the requirements of the Securities
Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.
Wetour Robotics Limited
By:
/s/ Nan Zheng
Name:
Nan Zheng
Title:
Chief Executive Officer
Date: September 4, 2026
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EX-99.1
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ea030468901ex99-1.htm
PRESS RELEASE DATED SEPTEMBER 1, 2026
Exhibit 99.1
Wetour Robotics Demonstrates sEMG-Vision System
Targeting Force and Occlusion Blind Spots in Physical AI Training
Dual-modal approach combines muscle activity
and first-person vision to capture richer human demonstration data for humanoid robots
AUSTIN, Texas, Sept. 1, 2026 (GLOBE NEWSWIRE) --
Wetour Robotics
Limited (NASDAQ: WETO) (“Wetour Robotics” or the “Company”), a Physical AI infrastructure and wearable robotics company,
today released a development demonstration of Orchestra combining surface electromyography (sEMG) with first-person vision to capture
richer human-hand data for robot learning.
The system is designed to address two limitations of vision-only capture:
cameras cannot directly observe how much force a hand applies, and they lose hand data when the hand is hidden behind an object or leaves
the field of view. Orchestra combines muscle activity with visual position so the two signals can complement each other at the edge.
“Physical AI needs more
than video. 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.
Orchestra is designed to add force-related information and continuity to human demonstration data,” said Nan Zheng, Chief Executive
Officer of Wetour Robotics.
Two Signals That Fill Each Other’s Blind Spots
Orchestra combines Conductor, an 8-channel sEMG wristband, with VisionLink,
a first-person camera. Vision provides spatial position and scene context. sEMG captures muscle activation, remains available during visual
occlusion and may provide a physical signal before visible movement begins. The development architecture is designed to fuse both streams
locally into one synchronized record of movement, effort and action timing.
In a representative internal carrying task, the vision-only pipeline
failed to locate the hand in 21.8% of frames, including a longest continuous dropout of 4.32 seconds. The architecture is designed to
use sEMG as a complementary signal during those missing visual intervals. The cross-modal correction strategy remains in validation.
What the Demonstration Shows
●
Continuous digital hand.
The current on-device model
outputs 20 joint angles rather than only classifying a small set of preset gestures. In an internal model benchmark, processing a one-second
sEMG window required 50.4 milliseconds with zero lookahead. This measurement reflects model processing time, not end-to-end system latency.
●
Force as a measurable dimension.
The force-estimation
pipeline is designed to convert sEMG into scale-calibrated, kilogram-equivalent grasp-force estimates. Calibration uses a scale as the
reference and fits the response to the wearer and wearing session. The pipeline has been validated end-to-end on synthetic data; validation
with live wristband force recordings remains under development.
●
Action-ready data.
The system is being developed
to layer events such as reach, grasp, hold and release over continuous hand motion, creating structured demonstrations for imitation learning
and robot training.
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Five real-world tasks.
The demo shows packing a lunch box, sorting
pills, disassembling a pen, measuring a drone with calipers and installing a drone propeller - tasks combining precision, changing hand
effort and frequent visual occlusion.
Why It Matters for Humanoid and Embodied AI
Human demonstrations are becoming an important input for training robots
in real environments. Wetour Robotics believes adding force-related data and greater resilience to visual occlusion can make that data
more useful for fine manipulation, compliant control and future human-robot collaboration.
Demonstration videos are available at www.wetourrobotics.com and on
the Company’s LinkedIn and X channels under Wetour Robotics and @WETO_IR_TEAM.
About Wetour Robotics Limited
Wetour Robotics Limited (NASDAQ: WETO) is a Physical
AI infrastructure and wearable robotics company headquartered in Austin, Texas. The Company is developing Orchestra, a Physical AI platform
that connects intelligent agents to the physical world through wearable sensors, visual intelligence, edge AI computing and connected
machines. Conductor is the Company’s wrist-worn neuromuscular interface, and VisionLink is its visual intelligence module.
Forward-Looking Statements
This press release contains forward-looking statements regarding the
development, integration, validation, performance, applications and commercialization of Orchestra, Conductor, VisionLink, sEMG-vision
fusion, force estimation, multimodal data capture and humanoid or embodied-AI applications. These statements are subject to risks including
technology-development and integration risk, differences between synthetic and real-world data, calibration and accuracy limitations,
competition, customer acceptance, capital requirements and other risks described in the Company’s filings with the U.S. Securities and
Exchange Commission. Actual results may differ materially. The Company undertakes no obligation to update forward-looking statements except
as required by law.
Investor Relations Contact
Annabelle Li
Head of Investor Relations
Wetour Robotics Limited
ir@wetourrobotics.com
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