Papers
17
Total Citations
414
H-Index
10
About
Pengbo Wang is a leading researcher in agricultural robotics and precision automation, with a focused body of work at the intersection of computer vision, machine learning, and robotic systems for greenhouse and field environments. His research has made substantial contributions to the development of autonomous harvesting robots across a diverse range of crops, including tomatoes, oyster mushrooms, apples, watermelons, and cherry tomatoes — addressing the pressing global challenges of labor shortages and rising agricultural costs. Wang's most cited work (89 citations) pioneers fruit pose recognition and intelligent grasping strategies for tomato harvesting, while his field-tested oyster mushroom harvesting robot (67 citations) and humanoid apple harvesting system (60 citations) demonstrate his ability to translate laboratory innovations into real-world deployable systems. His expertise extends to deep learning-based detection and segmentation techniques, including YOLO variants, SSD methods, and RGB-depth fusion architectures, enabling robots to perceive, localize, and interact with crops with remarkable accuracy and speed. With over 380 cumulative citations across his published works, Wang has established himself as a prominent voice in intelligent agricultural mechanization. His research consistently bridges theoretical computer vision advances with practical robotic engineering, making meaningful strides toward fully autonomous, scalable solutions for modern smart farming.
Research Focus
Key Achievements
Top Papers
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- 2A Field-Tested Harvesting Robot for Oyster Mushroom in Greenhouse67 citations · 2021
- 3A lab-customized autonomous humanoid apple harvesting robot60 citations · 2021
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- 10A combined visual navigation method for greenhouse spray robot10 citations · 2019