Papers
23
Total Citations
449
H-Index
11
About
Jun Chen is a robotics and automation researcher whose work spans agricultural robotics, robotic manipulation, and autonomous systems. He is perhaps best known for his pioneering contributions to robotic apple harvesting, where his research has systematically addressed the full engineering pipeline — from understanding fruit-branch dynamics to designing optimized picking patterns and purpose-built harvesting manipulators. His 2019 study on optimum picking patterns (74 citations) and subsequent work on a simplified 4-DOF harvester (62 citations) have helped establish foundational benchmarks in agricultural robotics, a field he also surveyed comprehensively in a widely read 2020 review. Chen's interests extend well beyond orchards: earlier work tackled autonomous tractor path tracking and robust neural-fuzzy control for robot manipulators, demonstrating a broad command of control theory and mobile robotics. His portfolio also includes inventive mechanical designs such as a steerable in-pipe robot and a rotating magnetic field system for capsule endoscopy navigation, reflecting a versatile engineering imagination. With over 380 cumulative citations across a decade of sustained output, Chen's research represents an important thread connecting precision agriculture, intelligent control, and biomedical robotics — making his work highly relevant to students and practitioners across multiple disciplines.
Research Focus
Key Achievements
Top Papers
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- 3Simplified 4-DOF manipulator for rapid robotic apple harvesting62 citations · 2022
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- 5Path tracking control of autonomous agricultural mobile robots32 citations · 2007
- 6Robust Adaptive Neural-Fuzzy Network Tracking Control for Robot Manipulator30 citations · 2014
- 7TECHNOLOGICAL DEVELOPMENT OF ROBOTIC APPLE HARVESTERS: A REVIEW22 citations · 2020
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- 9Development of an in-pipe robot with two steerable driving wheels14 citations · 2015
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