Bincheng Huang
Guangxi University, China Electronics Technology Group Corporation
Papers
3
Total Citations
48
H-Index
3
About
Bincheng Huang is a researcher at the intersection of agricultural automation and robotic control systems. His primary research areas include precision agriculture, computer vision for fruit detection, and adaptive control for space robotics. Huang’s most impactful contribution is the development of an improved YOLOv8 deep learning model for the simultaneous detection of mango fruits and fruiting stems, designed for deployment on edge devices—a breakthrough that enables real-time, on-site harvesting decisions. This work has garnered 38 citations, reflecting its significance in advancing automated fruit picking. In parallel, Huang has addressed the complex challenge of trajectory tracking in dual-arm space robots, proposing a finite-time adaptive control method that compensates for uncertain kinematics, dynamics, and deadzone nonlinearities. This research, cited 6 times, is critical for on-orbit servicing and coordinated manipulation tasks. Huang’s work bridges the gap between terrestrial agriculture and extraterrestrial robotics, demonstrating versatility in applying control theory and computer vision to real-world problems. His achievements highlight a commitment to deploying intelligent systems that operate reliably under uncertainty.
Research Focus
Key Achievements
Top Papers
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