Papers
3
Total Citations
131
H-Index
2
About
Hao Xia is a researcher at the forefront of agricultural robotics and intelligent automation, with a primary focus on deep learning and reinforcement learning for precision agriculture. His most impactful contribution is the development of a deep learning-based classification system for designing tomato harvesting robots, which achieved 115 citations by addressing the critical need for accurate, real-time maturity level classification—a key bottleneck in precision picking. This work replaced slow, error-prone traditional methods with a robust neural network approach, significantly advancing automated harvesting. More recently, Xia has pioneered the SBP-YOLOv8s-seg network for safflower picking point localization during the full harvest period, a 2024 study that demonstrates his continued innovation in crop-specific robotic vision. He has also tackled mapless navigation for mobile robots, proposing an Improved Soft Actor-Critic (ISAC) algorithm that enhances training efficiency and convergence speed over standard SAC. With a growing citation footprint and a clear trajectory from foundational classification systems to cutting-edge segmentation and navigation, Hao Xia’s research is shaping the next generation of intelligent, autonomous agricultural machinery.
Research Focus
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Top Papers
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