Yaya Chen
Papers
5
Total Citations
52
H-Index
3
About
Yaya Chen is a robotics and agricultural automation researcher whose work sits at the intersection of intelligent robotic systems and precision horticulture. Drawing on expertise in motion planning, computer vision, and simultaneous localization and mapping (SLAM), Chen has made notable contributions to automating complex agricultural tasks in unstructured natural environments. Chen's most cited work (29 citations) introduced an improved RRT-Connect algorithm for obstacle-avoidance path planning in fruit tree pruning manipulators, addressing one of the core challenges of deploying robotic arms in unpredictable outdoor settings. A significant thread of Chen's research focuses on rubber tapping automation — a labor-intensive agricultural process — encompassing tapped area detection using Mask R-CNN (10 citations), a semantically enhanced 3D LiDAR SLAM system called Se-LOAM for navigation in rubber plantations (8 citations), and tapping line detection leveraging improved YOLOv8 with RGB-D fusion. Most recently, Chen has extended this work into cutting dynamics modeling using finite element methods, reflecting a growing interest in the biomechanical dimensions of robotic harvesting. With over 50 cumulative citations, Chen's research provides a comprehensive technical foundation for next-generation agricultural robots, offering practical solutions to real-world automation challenges in farming.
Research Focus
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Top Papers
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