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Foremost in collaborative robots, ‘Neuromeka’Opening of Collaborative Robot Deep Learning Research Centre with POSTECH …
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승인 2018.10.18  23:12:43
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▲ collaborative robot Indy
Neuromeka is one of a handful of dominant Korean companies in the field of collaborative robots.

Powered by their real-time embedded fieldbus based robot controller, robot simulation and control software, the company has pioneered the collaborative robot market with their ‘easy and safe to use at a low cost industrial robot’ Indy series.

With its innovative algorithms, the collaborative robot Indy is loaded with safety guarantees. The high efficiency and low-cost robot features impedance control that is sensitive to the force intended by the user and collision avoidance using algorithms without the need for sensors for the prevention of accidents or injuries.

Key functions include joint velocity and torque control with observer based collision detection algorithms to allow safe movement and impedance control using direct torque control and nonlinear H-∞ optimal control.

Additionally, the product allows direct task teaching using F/T sensors, teaching using physical HRI devices, online and offline robot programming based on visual apps, and intuitive HRI devices.

Along with their collaborative robots, neuromeka has also announced their Delta robot, LASER series. The LASER is a parallel robot that delivers world-class performance and services and includes a line-up featuring small, medium, and large 4-axis, high speed delta robots; 2-axis parallel robots capable of high capacity handling; and 6-axis delta robots capable of handling solid items.

▲ Neuromeka opened the Cobot Deep Learning Research Center in conjuction with the Robotics Laboratory headed by Prof. Wan Kyun Chung at Korea’s POSTECH.
Neuromeka opened the Cobot Deep Learning Research Center in conjuction with the Robotics Laboratory headed by Prof. Wan Kyun Chung at Korea’s POSTECH, where research is underway to develop a wide range of new technologies that can be applied to collaborative robots.

Over the last few months, both groups have begun research to apply deep learning techniques to collaborative robots. Initial results have yielded real-time deep learning-based signal processing technology that has been applied to significantly improve the sensitivity and accuracy of existing collision detection algorithms, and the use of a single camera to approximate the 3-dimensional location and positioning information of an object.

These results can be used to implement a low cost, high performance vision system. In addition, recently, by solidifying their collaborative robot solutions supply capacity through its merger with Auto Power, neuromeka has made an expansion in the market, while maintaining their technological superiority in research and development through industry-academia cooperation with POSTECH. Through these efforts, they are dominating the domestic collaborative robot landscape.

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