华硕首款人形机器人Gallop11月13日亮相：在工厂学习每块主板约20秒装15件配件、目标20秒内成功率99.5%
华硕于 2026 年 11 月 13 日在公司新闻室发布其首款人形机器人 Gallop，由共同首席执行官许先越在 CNBC 上介绍。Gallop 正在华硕集团一家电子代工厂的真实工位上学习作业。
该工位的任务是为每块主板装配 15 件配件，其中不少是装在透明薄袋里的小件，Gallop 目前的速度约为每块主板 20 秒。华硕设定的目标是 20 秒内成功率达到 99.5%，与对人工的同一标准一致，公司同时说明这一数字是目标、并非当前成功率。
Gallop 机身内装有一台英伟达 Jetson AGX Thor 计算机，使用标准机器人软件。它通过头部摄像头观看熟练工人的操作，并结合模拟变化、虚拟现实引导练习与在岗反馈来学习。
该项目于 2026 年初启动，开发至今不足一年。华硕计划 2027 年开展客户试点，在 Computex 2027 上作客户展示，目标于 2028 年下半年上市。
华硕未公布 Gallop 的售价、单位成本与产量。按公司公布的节奏，这款双臂人形机器人将先在自家集团工厂的工位上接受与人工同一标准的考核，再走向客户试点。
（来源：华硕）
ASUS Unveils Gallop, Its First Humanoid Robot, on November 13: It Is Learning to Pack 15 Motherboard Accessories in About 20 Seconds a Board, With a Target of 99.5 Percent Success Within 20 Seconds
ASUS unveiled Gallop, its first humanoid robot, in a company pressroom post on November 13, 2026, introduced by co-chief executive S.Y. Hsu on CNBC. Gallop is learning a real workstation at an ASUS group electronics manufacturing plant. The job is packing 15 motherboard accessories per board, many of them small parts in thin clear bags, at about 20 seconds per board. ASUS's target is 99.5 percent success within 20 seconds, the same standard it holds a person to, and the company has not disclosed how often Gallop succeeds today. Gallop runs on a single Nvidia Jetson AGX Thor computer inside the robot and uses standard robotics software. It learns by watching skilled workers through head cameras, along with simulation variations, VR-guided practice and on-the-job feedback. The program started in early 2026, so Gallop has been in development for less than a year. Customer pilots are planned for 2027, a customer showing is planned at Computex 2027, and market availability is targeted for the second half of 2028. ASUS disclosed no price, unit cost or production volume for Gallop. The two-armed robot is being judged against the person doing the same factory job, rather than against a demonstration.
(Source: ASUS)
来源：华硕
发布：GSM·美国（发布链接）
图片来源：图：一台白色人形社交机器人。GeneralAB13，CC BY-SA 4.0，经 Wikimedia Commons。 / Photo: GeneralAB13, CC BY-SA 4.0, via Wikimedia Commons.
GSM Global · 本篇英文版 English edition of this story
