Papers
3
Total Citations
27
H-Index
3
About
Ye Zeng is an emerging researcher specializing in agricultural robotics, with a particular focus on autonomous navigation, path planning, and motion control for orchard mowing robots. Working at the intersection of robotics and precision agriculture, Zeng has made notable contributions to solving the complex challenges posed by unstructured orchard environments, where irregular terrain, narrow corridors, and unpredictable obstacles present significant technical hurdles for autonomous systems. Among Zeng's most impactful contributions is the development of an improved artificial potential field algorithm incorporating elliptic repulsion scope boundary constraints, enabling safer and more reliable local path planning for mowing robots in dense orchard settings — a work that has already garnered 12 citations since its 2023 publication. Complementing this, Zeng introduced a cascaded Model Predictive Control framework combined with anti-slip drive control to address longitudinal slippage during path tracking, achieving high-precision autonomous navigation under challenging adhesion conditions (11 citations). More recently, Zeng explored safe corridor and quadratic programming approaches to further refine local planning under kinematic constraints. Collectively, these contributions signal Zeng as a promising voice in agricultural automation, offering practical, safety-conscious solutions that advance the field of orchard robotics.
Research Focus
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Top Papers
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