Zhenguo Zhang
Papers
5
Total Citations
61
H-Index
4
About
Zhenguo Zhang is a pioneering researcher specializing in agricultural robotics, precision automation, and computer vision, with a particular focus on developing intelligent systems for safflower harvesting. His work addresses some of the most challenging problems in crop robotics, including accurate detection and localization of small, densely clustered plant structures under complex natural conditions such as varying illumination, occlusion, and near-colored backgrounds. Zhang's most impactful contributions include developing the SDC-DeepLabv3+ algorithm for precise safflower filament localization and an improved Faster R-CNN model incorporating split attention mechanisms for robust filament detection in uncontrolled field environments — both earning 17 citations each. His filament-necking localization method, combining improved particle swarm optimization with a rotated rectangle algorithm, further demonstrates his innovative problem-solving approach, also garnering 17 citations. Beyond detection, Zhang has advanced full-system robotic autonomy through a sophisticated headland-turning navigation framework integrating binocular cameras, differential satellites, and inertial sensors. His most recent work explores dual-arm cooperative path planning to overcome efficiency bottlenecks in single-arm harvesting systems. Collectively, Zhang's research is laying essential groundwork for fully autonomous, high-efficiency agricultural harvesting robotics.
Research Focus
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