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About

Zhiliang Kang is a leading researcher in agricultural robotics and intelligent automation, with a focus on machine vision and motion planning for fruit and vegetable harvesting. His work bridges the gap between computer vision and robotic manipulation, enabling machines to operate effectively in complex, unstructured natural environments. Kang’s most cited paper (40 citations) introduces a computer vision system for automatic recognition of pointer instruments, optimizing data sets to overcome background interference—a critical advancement for industrial substation robots. He has also made significant contributions to agricultural robotics, including collision-free motion planning for a six-link manipulator used in citrus picking (18 citations), and an efficient combined multipoint picking scheme for tea buds (9 citations). His earlier work on citrus recognition in real scenarios (4 citations) and intelligent watermelon identification (2 citations) laid the groundwork for fruit-harvesting robots, addressing key challenges in low identification rates and positioning accuracy. With a total of over 70 citations across his most-cited works, Kang’s research is instrumental in advancing the precision and reliability of robotic systems for both industrial and agricultural applications, directly impacting the development of smarter, more autonomous harvesting technologies.