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

10
H-Index
17
Papers
414
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Fruit pose recognition and directional orderly grasping strategies for tomato harvesting robots
89 citations · 2022
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 42
🏛 Institutions: Soochow University, Northwestern Polytechnical University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago