Fengyi Cheng

Papers

Total Citations

244

H-Index

About

Fengyi Cheng is a leading researcher in agricultural robotics, with a primary focus on intelligent harvesting systems for fruit crops. His work centers on developing vision-guided robotic platforms and advanced navigation algorithms to automate the delicate task of apple picking. Cheng’s most influential contribution is his pioneering paper, “Automatic recognition vision system guided for apple harvesting robot” (2011), which has accumulated over 230 citations, establishing a foundational framework for integrating computer vision with robotic manipulators in orchard environments. This work addresses the critical challenge of accurately detecting and localizing fruit for automated harvesting. Additionally, Cheng has advanced obstacle avoidance strategies for agricultural manipulators, notably through his improved artificial potential field method (2012, 2013), which adapts traditional path-planning algorithms to the unique constraints of apple-growing environments, such as irregular tree canopies and fruit-laden branches. His research bridges the gap between theoretical robotics and practical agricultural applications, offering scalable solutions to labor shortages in fruit harvesting. Cheng’s contributions continue to influence the design of autonomous agricultural systems, making him a key figure in the field of precision agriculture and robotic fruit picking.