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New Humanoid Robot Enhances Human-like Dexterity in Industrial Applications

The humans behind H-u-m-a-n-o-i-d.com June 11, 2026 2 min read

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At the IEEE International Conference on Robotics and Automation (ICRA 2026) in Vienna and COMPUTEX Taipei 2026, a Vietnamese technology company, VinRobotics, introduced the VR-H3 humanoid robot, designed for industrial and operational use. With advanced mobility, perception, and manipulation capabilities, the VR-H3 boasts over 31 actuators and dual onboard edge computers. This humanoid can navigate complex environments, interact with individuals, transport materials, lift payloads, and execute assembly tasks in real-world scenarios.

VinRobotics, a subsidiary of Vingroup, recently unveiled its third-generation humanoid robot, the VR-H3, to cater to industrial automation needs. Equipped with more than 31 actuators and two onboard edge computers for quick decision-making, the VR-H3 can handle payloads of 13 to 17 pounds, execute assembly tasks, and adapt to dynamic environments efficiently. Developed entirely in-house, the robot’s mechanical architecture, computing infrastructure, and sensing systems are optimized for performance and control.

The VR-H3’s teleoperation capabilities were showcased at ICRA 2026, featuring motion-capture technology integrated into a virtual reality headset for real-time remote control. VinDynamics, another Vingroup subsidiary, revealed Dyno, their debut humanoid robot, designed for security, surveillance, and household support applications. Dyno combines advanced AI, perception, and manipulation technologies to operate autonomously in intricate environments, interact naturally with people, and perform tasks requiring situational awareness and precise handling.

In a live demonstration, Dyno displayed its functionality as an autonomous guide, engaging visitors and responding to queries using multilingual speech and real-time awareness. VinDynamics also presented cutting-edge technologies such as the VDM 80 high-performance actuator and an AI training dataset to enhance humanoid learning and performance in real-world scenarios. Jijo, an automotive and business journalist from India with a background in History and Journalism, brings diverse experience from news agencies and national newspapers. In his free time, he enjoys off-roading, world travel, political discussions, and language mentoring.

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