Chang-Ru Chen

National Taiwan University of Science and Technology

Papers

Total Citations

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About

Chang-Ru Chen’s research centers on robotics, automation, and visual servoing, with a focus on enhancing industrial manipulators for precision tasks. A key contribution is the development of a vision-based SCARA (Selective Compliance Assembly Robot Arm) system for spanner fetching and placing, detailed in their 2016 paper, which has garnered 11 citations. This work demonstrates a practical application for traditional factories, featuring a 50 cm working range and four degrees of freedom. By integrating visual feedback for object detection and manipulation, Chen’s system improves accuracy and efficiency in pick-and-place operations, addressing real-world manufacturing challenges. Their approach bridges computer vision and robotic control, offering a scalable solution for automating repetitive tasks. While early in their career, Chen’s research highlights the potential of low-cost, adaptable robotic systems for industry, contributing to the broader field of service and industrial robotics. Their work serves as a foundation for further advancements in visual servoing and automation.