[News] Ennostar Expands into Robotics, Unveils Mini/Micro LED Human-Machine Interface Displays

On August 20, Ennostar teamed up for the first time with edge computing leader ADLINK to jointly participate in the 2025 Taiwan Robotics and Smart Automation Show, targeting the fast-growing automation and robotics market. Ennostar stated that the exhibition highlights Mini LED and Micro LED human-machine interface (HMI) displays and automation sensing solutions, demonstrating the company’s integration strengths in smart sensing and advanced display technologies, which marks its official entry into the emerging robotics application markets.

Ennostar noted that the company continues to drive its “dual value-added engine” transformation strategy while strengthening its “3+1 long-term development strategy,” with robotic automation regarded as a key application scenario for smart sensing. As generative AI accelerates the deployment of humanoid robots and autonomous mobile vehicles, the global robotics market continues to expand. Going forward, Ennostar will collaborate with international ecosystem partners to deepen resource integration, delivering integrated solutions in visualization and intelligent sensing with a focus on the robotics automation market.

At the show, Ennostar unveiled two core technology offerings. Human-machine interface displays use Mini LED and Micro LED technologies with high contrast, low power consumption, high curvature, and customizable sizes, enabling diverse applications such as hidden displays to meet the dynamic display requirements of smart robots.

Ennostar also presented non-contact temperature sensing and announced plans to expand into core sensing technologies such as vision, touch, and ranging to address the surging sensing needs of automation robots.

Ennostar emphasized that by leveraging its technological strengths in advanced display and intelligent sensing, the company aims to capture emerging opportunities in the robotics market on the strength of its ecosystem partners.

(Photo credit: Ennostar)

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