Papers
40
Total Citations
1,648
H-Index
17
About
Chengliang Liu is a pioneering researcher at the intersection of agricultural robotics, computer vision, and intelligent manufacturing systems. Best known for his foundational work in vision-based robotic harvesting, his 2016 review of key vision control techniques for harvesting robots has become a landmark reference in the field, accumulating nearly 400 citations. Liu's research has consistently tackled one of precision agriculture's most stubborn challenges: enabling autonomous robots to reliably detect, locate, and harvest fruits in complex, unstructured greenhouse environments. His contributions span fruit recognition algorithms using AdaBoost classifiers and feature image fusion, dual-arm robotic systems for tomato harvesting, and sophisticated solutions for grasping occluded fruits through 3D shape reconstruction — together drawing hundreds of citations from the global robotics community. Beyond agriculture, Liu has made significant inroads into industrial IoT and smart manufacturing, exploring cloud-assisted robotics and cognitive systems for Industry 4.0 material handling. His 2024 work on LiDAR–inertial–ultrasonic SLAM demonstrates his commitment to cutting-edge autonomous navigation for plant factories. With over 1,300 cumulative citations across his most-cited works alone, Liu's interdisciplinary contributions have meaningfully advanced both agricultural automation and intelligent industrial systems, making his research essential reading for roboticists and precision agriculture engineers alike.
Research Focus
Key Achievements
Top Papers
- 1A review of key techniques of vision-based control for harvesting robot394 citations · 2016
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- 5Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion108 citations · 2016
- 6Dual-arm Robot Design and Testing for Harvesting Tomato in Greenhouse100 citations · 2016
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