Hui Geng

Dalian Polytechnic University, Tarim University

Papers

Total Citations

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About

Hui Geng is a researcher at the forefront of intelligent robotics and agricultural automation, with key contributions spanning autonomous navigation and precision fruit recognition. Geng’s work addresses critical challenges in real-world robotic systems, particularly in path planning and perception under complex conditions. Their most cited paper, “Modified A* algorithm for path smoothing and obstacle avoidance” (2024, 3 citations), introduces an enhanced A* algorithm that overcomes the traditional method’s limitations in real-time performance and path smoothness, offering a more practical solution for autonomous robot navigation in cluttered environments. Building on this, Geng’s recent study “Apple estimation and recognition in complex scenes using YOLO v8” (2025, 1 citation) tackles the pressing issue of low detection accuracy in agricultural robotics caused by natural occlusions and variable lighting. By leveraging the YOLO v8 deep learning framework, this work improves the reliable identification of ripe apples, directly supporting the development of efficient, adaptable fruit-picking robots. Though early in their career, Geng’s research demonstrates a clear trajectory toward integrating robust perception with intelligent motion planning, laying essential groundwork for next-generation autonomous systems in both industrial and agricultural settings.