Papers

7

Total Citations

130

H-Index

5

About

Zhenghua Ma is a leading researcher in agricultural robotics and computer vision, whose work is transforming automated fruit harvesting. His primary research focuses on developing intelligent visual perception systems for robots operating in complex, unstructured orchard environments. Ma’s major contributions include pioneering methods for identifying apple growth forms and isolating near-large fruits from cluttered orchard images, directly addressing the challenges of uneven lighting, branch occlusion, and overlapping fruit. His highly cited 2022 survey on fruit and vegetable recognition against similar-color backgrounds provides a critical roadmap for the field, synthesizing solutions to one of the most persistent problems in agricultural robotics. With his most-cited paper accumulating 43 citations, Ma’s work has demonstrably shaped the trajectory of precision agriculture. Beyond vision systems, he has advanced robot control theory, developing robust sliding-mode and variable structure controllers to handle load uncertainties and improve manipulator tracking precision. His early work on mobile robot obstacle avoidance, fusing binocular stereo vision with infrared ranging, laid the groundwork for his current focus. Through this integrated approach—combining cutting-edge computer vision with adaptive control—Zhenghua Ma is engineering the next generation of autonomous harvesting robots.

Research Focus

Key Achievements

5
H-Index
7
Papers
130
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
A visual identification method for the apple growth forms in the orchard
43 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Changzhou University, Jiangsu University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago