Jifeng Qin

Northwest Institute of Mechanical and Electrical Engineering, Institute of Soil and Water Conservation

Papers

Total Citations

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About

Jifeng Qin is an emerging researcher specializing in agricultural robotics, autonomous navigation, and precision agriculture, with a particular focus on developing intelligent systems for orchard environments. His work addresses critical challenges in agricultural automation, including reliable robot localization, obstacle avoidance, and coordinated multi-robot operations in complex, unstructured orchard settings. Qin's most notable contributions include pioneering integrated navigation frameworks that fuse LiDAR, IMU, and GNSS technologies to dramatically improve the positioning and path-planning reliability of agricultural robots. His development of a collaborative spraying-dosing robot group system — enabling seamless task handoff when a spraying robot depletes its chemical supply — represents a practical and impactful solution to real-world agricultural inefficiencies. Additionally, his application of Double-DQN reinforcement learning algorithms to path-tracking control in orchard traction spraying robots demonstrates his innovative use of deep learning to enhance vehicle stability and precision. With multiple papers accumulating citations since 2022, Qin's research is gaining recognition within the agricultural engineering and robotics communities. His interdisciplinary approach, bridging sensor fusion, machine learning, and autonomous systems, positions him as a promising contributor to the future of smart, automated precision agriculture.