--- title: "Asus unveils Gallop, its first humanoid robot for packing motherboards" description: "Asus has unveiled Gallop, its first humanoid robot for the electronics industry. Based on the Nvidia Jetson AGX Thor, it is learning to pack motherboards with 99.5% target accuracy. A full market release is scheduled for the second half of 2028." date: 2026-11-13T16:04:21.159Z lang: en url: https://xab.info/en/posts/asus-gallop-humanoid-robot-motherboard-packing tags: [asus, humanoid-robot, gallop, nvidia-jetson, electronics-manufacturing, physical-ai, robotics] author: "Alexander Buran" publisher: "XAB.info" --- # Asus unveils Gallop, its first humanoid robot for packing motherboards ![Humanoid robot Asus Gallop with a white chassis on a black background during production](https://xab.info/media/2026/11/13/asus-gallop-chelovekopodobnyj-robot-upakovka-materinskikh-plat/asus-gallop-chelovekopodobnyj-robot-upakovka-materinskikh-plat-1.webp) ## Key Points - Asus unveiled Gallop, its first humanoid robot for electronics manufacturing operations - The robot is learning to pack motherboards: 15 components, ~20 seconds per operation, 99.5% target accuracy - Platform built on Nvidia Jetson AGX Thor; software architecture is four-tiered with fixed interfaces - Training methods include operator observation, software simulation, and VR control - Pilot projects scheduled for 2027, with full market entry in the second half of 2028 Taiwanese corporation Asus has announced the unveiling of Gallop, its first humanoid robot designed to perform manufacturing operations in the electronics industry. As of the publication date, the robot is undergoing testing at Asus's own factory, where it is learning to pack boxes with motherboards. The task assigned to Gallop during the initial training phase involves organizing 15 different components into boxes, many of which are small parts in thin, transparent plastic bags. The duration of one operation is approximately 20 seconds per motherboard, with a target accuracy of 99.5% while adhering to time standards. ### Architecture: Four levels of software control based on Nvidia Jetson AGX Thor Gallop is a humanoid torso with two manipulator arms mounted on a fixed base. The robot's software and hardware platform is built on a single Nvidia Jetson AGX Thor computing module located directly inside the body. The software architecture is divided into four levels: a planner analyzes the environment and breaks the task into a sequence of actions; a separate oversight system monitors operations and revises the plan if necessary; a skills level is responsible for movement, grasping, and object placement; and a control level manages the hands and manipulators directly. Fixed interfaces are provided between the levels, allowing AI models to be swapped without completely redesigning the robot. ### Training: From observing operators to VR-control Gallop's training process combines several methods. First, the robot observes experienced employees who, with their consent, use small head-mounted cameras to record manufacturing operations. Then, a software simulation generates variations of recorded actions, helping the system adapt to changing conditions. Additionally, an operator in a VR headset and gloves can directly control the robot while performing operations with the same parts and cameras used in the actual workplace. This multi-level approach to training is intended by the developers to accelerate the transfer of skills to other robots and reduce training time for autonomous labor. ### Hardware: Proprietary manipulators and outsourced components Asus develops the robot's body and manipulators itself, including tactile-sensitive hands and fingers. Motors and other standard components are sourced from third-party suppliers. Over the next year, Asus plans to equip Gallop with its own multi-fingered hand with tactile sensitivity, install it on a wheeled platform, and demonstrate it to potential customers at Computex 2027. ### Timeline: From the 2026 launch to market arrival in late 2028 The Gallop development program started in early 2026, less than a year ago. Pilot projects with clients are scheduled for 2027, with a full market launch expected in the second half of 2028. The initial area of application will be electronics manufacturing, though the company is considering the future use of Gallop in hospitals and other service sector institutions. Asus emphasizes that the robot is not intended to take jobs away from humans, but rather to free them from the monotonous, routine operations that currently occupy a significant portion of working time on production lines. ## Fact-Check & Sources - [Asus представила андроида Gallop для упаковки материнских плат — теперь все вопросы по некомплекту к нему](https://3dnews.ru/1151266) - Primary source containing a full description of the robot, architecture, training methods, and project timeline. Data is consistent with the official Asus announcement. - [Asus представила андроида Gallop для упаковки материнских плат — теперь все вопросы по некомплекту ...](https://3dnews.ru/1151266/asus-predstavila-androida-gallop-dlya-upakovki-materinskih-plat-teper-vse-voprosi-po-nekomplektu-k-nemu) - Duplicates source 1 (same 3dnews.ru page with a different URL slug). Contains no additional or contradictory facts. ## FAQ ### What is Gallop and what is it designed for? Gallop is Asus's first humanoid robot, featuring a torso with two manipulator arms on a fixed base. It is designed to perform manufacturing tasks in the electronics industry, particularly packing motherboard boxes. ### What computing components are used in Gallop? The platform is built on an Nvidia Jetson AGX Thor module housed inside the robot. Asus sources motors and standard components from third parties while developing the body and manipulators in-house. ### How is Gallop trained? Training combines three methods: observing experienced operators via head-mounted cameras (with employee consent), software simulations generating action variations, and direct operator control using VR headsets and gloves. ### When will Gallop be released? Pilot projects are planned for 2027, with a demonstration at Computex 2027 expected next year. A full commercial launch is targeted for the second half of 2028. ### Will the robot replace human workers? Asus states the goal is not to displace workers but to relieve them of monotonous, routine tasks. Initial applications are in electronics production, with potential future uses in hospitals and service sectors.