Papers
6
Total Citations
117
H-Index
5
About
Yangfan Li is an interdisciplinary robotics researcher whose work bridges agricultural automation and advanced soft robotics systems. Li has made notable contributions to autonomous navigation for field robots, most prominently demonstrated through research on LiDAR SLAM-based navigation for orchard spraying robots using NDT_ICP point cloud registration — a paper that has rapidly accumulated 87 citations since 2024, reflecting its significant practical relevance to precision agriculture. Beyond field robotics, Li has pursued innovative directions in soft and compliant robotic systems, exploring dielectric elastomer actuators (DEAs) as artificial muscle alternatives, 3D-printable variable-stiffness ball joints for robotic linkages, and hybrid soft-rigid gripper architectures featuring flexible metal endoskeletons. These contributions address a critical challenge in the field: enabling soft robots to handle both delicate and heavy-load tasks simultaneously. More recently, Li has extended this work toward intelligent food-handling systems through automated gesture planning for reconfigurable soft grippers. Collectively, Li's research portfolio demonstrates a sophisticated command of sensor-driven autonomy, smart materials, and biomimetic actuation, making meaningful contributions to next-generation robots designed for real-world agricultural and industrial deployment.
Research Focus
Key Achievements
Top Papers
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- 3Soft Printable Robots With Flexible Metal Endoskeleton7 citations · 2024
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