ASUS's Humanoid Robot Targets Human-Pace Factory Packing by 2027

ASUS says its first humanoid robot, Gallop, is learning to pack 15 motherboard accessories at one of the group's electronics factories, with a target of 99.5% success within 20 seconds per board — the same speed-and-success standard the company applies to human workers. The company detailed the program on November 13, 2026, and stressed the figures are targets, not achieved results.

The workstation isn't a demo-friendly one. Many parts arrive in thin, clear bags, which trips up simple grippers. ASUS picked the station deliberately: it wants to know whether the robot can handle most of a job without a person standing beside it. The development program began in early 2026, run by the Humanoid Robotics unit inside the Physical AI Solutions Business Group.

For people leaders, the more consequential fact is how the robot learns. Experienced workers — with their consent — wear head-mounted cameras so their demonstrations capture how the job is actually done. Simulation then generates variations of those recordings, and an operator in a VR headset and gloves guides Gallop through practice with the same parts and cameras used at the real station. Recordings from deployed robots feed back into training.

What changes for the workers who teach it?

ASUS positions the robot for repetitive, physically demanding stations that are difficult to staff, not as a replacement for workers. Employees who teach Gallop would move into setting up, supervising and improving robots, the company said. That's a reskilling claim HR teams in electronics manufacturing will hear more often as pilots spread.

The company claims a data advantage most robotics firms lack: its own electronics manufacturing services factories supply the test environment. Competitors typically must rent space. ASUS says its edge is the right data from real stations, real parts and real quality rules.

Why the four-layer software design matters

Gallop's software splits into four layers:

• A planner interprets the scene and divides the job into steps.
• An AI supervisor checks each step and replans after a problem.
• A skills layer handles reaching, grasping and placing.
• A control layer moves the arms and hands precisely and stops them when something is wrong.

Fixed interfaces between the layers let ASUS swap AI models without rebuilding the robot. The system runs on one NVIDIA Jetson AGX Thor computer inside the robot, using standard robotics software. ASUS designs the body and a touch-sensing dexterous hand in-house; motors and other standard components come from established partners.

The current robot uses a fixed base and two arms for stationary pick-and-place work, and the in-house hand isn't integrated yet. ASUS's broader argument for the humanoid form: arms and dexterous hands can use existing workstations, tools and trays designed for people, avoiding a factory rebuild around the robot. The company concedes not every task needs a humanoid.

When do customers — and HR — see proof?

The full loop already works end to end: a person shows the task, the robot learns it, and ASUS tests it on the line. But the commercial clock runs through 2027 and 2028. ASUS plans to integrate the hand, add wheels, and show Gallop at Computex 2027, with customer pilots in the same year. Market availability is targeted for the second half of 2028.

Electronics manufacturing is the first market. ASUS expects pick-and-place skills learned in one job to transfer to others, pointing to possible later uses in hospitals and service sites.

The pilots carry the real burden of proof. ASUS has made consistency its threshold for broader use: the working training loop is only the starting point, and the 2027 pilots must show repeatable, factory-quality results under everyday production conditions before anyone books labor savings.