Kuang Yin
Papers
4
Total Citations
8
H-Index
2
About
Kuang Yin is a researcher focused on advancing industrial robotics, particularly in the areas of robot control, perception, and automation. Their work addresses critical challenges in manufacturing, including real-time inspection, intuitive human-robot interaction, and autonomous manipulation. A key contribution is the development of a phased optimization method for robot dragging teaching without torque sensors, enabling more flexible and accessible programming for industrial robots. Yin also proposed a real-time wavelet transform inspection algorithm for switchgear circuit breaker trolleys, enhancing compliance verification through robust signal processing. Additionally, they have contributed to vision-based pose estimation for randomly placed workpieces and improved motion path planning for sorting robots using an extended RRT-Connect algorithm, which accelerates autonomous obstacle avoidance. While each of these four 2021 papers has garnered 2 citations, their collective focus on practical, sensor-efficient solutions for real-world automation highlights Yin’s commitment to bridging the gap between theoretical robotics and industrial application. This work is particularly valuable for students and researchers exploring cost-effective robot teaching, inspection, and path planning in manufacturing environments.
Research Focus
Key Achievements
Top Papers
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