ASUS Gallop Humanoid Robot Takes Its First Factory Job Packing Motherboard Parts
ASUS has unveiled Gallop, its first humanoid robot, and put it straight to work packing motherboard accessories at one of its own electronics factories. The fixed-base, two-armed robot runs on a single NVIDIA Jetson AGX Thor computer, learns by watching skilled workers, and is targeting 99.5% success within 20 seconds per board — the same standard ASUS holds a human worker to. Customer pilots are planned for 2027, with market availability targeted for the second half of 2028.
ASUS Gallop Humanoid Robot Takes Its First Factory Job Packing Motherboard Parts
ASUS has unveiled Gallop, its first humanoid robot, and given it a job on day one. Instead of a staged demonstration, the robot is learning to pack motherboard accessories at a real workstation inside one of the ASUS group's own electronics manufacturing factories. Co-CEO S.Y. Hsu introduced Gallop on CNBC on November 13, 2026, and ASUS corporate vice president Dr. Albert Chang set out the details the same day in a company blog post.
The debut is deliberately unglamorous. Gallop's first assignment is packing 15 small motherboard accessories, many of them sealed in thin, transparent plastic bags, at a station where each board takes about 20 seconds. ASUS says its target is 99.5% success within 20 seconds, the same standard it holds a human worker to. That figure is a target the company has set for itself, not a result it has measured and published so far.
A real workstation, not a demo
Videos of humanoid robots dancing, sorting blocks and folding laundry are everywhere now. ASUS argues that a factory manager asks a different question: can the robot do this station, for a full shift, to the site's quality standard? That is the question Gallop was built to answer.
Most factories are built around people, with stations, tools and trays sized for human hands. Traditional automation is excellent at fixed, high-volume tasks but struggles with work that changes from one production run to the next. A robot with two arms and dexterous hands can work at the same stations, with the same tools, so the factory does not have to be rebuilt around it. ASUS chose the packing station precisely because it is hard: small, thin and soft parts are exactly what a simple gripper cannot handle.
The company also applies a rule of its own to the project. A robot has to take on most of a job — if a person still has to stand beside it the whole time, nobody gains anything. The full loop now works, ASUS says: a person shows the task, the robot learns it, and the team tests it on the line.
How Gallop learns from workers
Teaching Gallop works much like training a new colleague, and the workers are the teachers. ASUS starts from leading open AI models that already understand how hands and objects behave, rather than building its own giant model. Experienced workers then wear a small head camera, with their consent, so the robot can learn how the job is really done.
Simulation generates variations of each demonstration, so small changes on the line do not surprise the robot. An operator in a VR headset and gloves then guides Gallop through the task hands-on, using the same parts and the same cameras as the real station. Once deployed, what the robot records feeds back into its training. The lesson for ASUS, Chang wrote, is that the edge is not more data but the right data: a real station, real parts and real quality rules.
Four layers of AI on one Jetson Thor computer
Inside, Gallop works in four layers. A planner looks at the scene, understands the job and breaks it into steps. A supervisor, a second AI, checks every step and re-plans when something goes wrong. A skills layer handles reaching, grasping and placing, and a control layer moves the arms and hands precisely and stops instantly if anything is wrong.
The layers talk to each other through fixed interfaces, so when a better AI model arrives, ASUS can swap it in without rebuilding the robot. All of it runs on a single NVIDIA Jetson AGX Thor computer inside the robot, using standard robotics software. NVIDIA's hardware sits at the centre of the current AI build-out, and Jetson Thor is the company's platform for physical AI and robotics, as covered in Innopark IT's report on the Nvidia fallout across Southeast Asia's AI boom.
ASUS designs the robot's body and its hand itself. The hand is the hardest part of any humanoid and is still scarce worldwide, so the company builds its own in-house, with a sense of touch. Motors and other standard components come from established partners.
What comes next
Today Gallop works from a fixed base with two arms; a wheeled version comes next. Over the coming year ASUS plans to bring its own dexterous hand into the robot, put it on wheels and show it to customers at Computex 2027. Customer pilots are planned for 2027, and the company is targeting the second half of 2028 for market availability.
The Gallop programme started in early 2026. Electronics manufacturing comes first, because it is the industry ASUS knows best, and the company says skills learned at one workstation can carry over to the next, since many jobs share the same pick-and-place movements. From there it sees the robot moving into hospitals and service sites over time.
ASUS is clear that Gallop is not meant to replace workers. It is designed for the repetitive, physically demanding stations that are hardest to staff, and the people who teach it move into setting up, supervising and improving the robots. What ASUS has not published yet is equally notable: no measured success rate, no height, weight, payload or battery-life figures, and no price. A demo shows a robot can do something once; a factory needs one that does the job every day. That is the standard ASUS has set for Gallop, and it says it will keep sharing its progress against it.
Sources
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