Max Robotics — Global Service Robot Directory + US Certification

About

Hong-Mei Sun is a leading researcher in agricultural robotics and computer vision, specializing in the development of fast, lightweight detection algorithms for fruit and vegetable picking robots. Her major contributions center on overcoming the dual challenges of complex natural scenes—such as backlighting, leaf occlusion, and overlapping fruit—and the computational constraints of embedded robotic platforms. Sun pioneered the "Light-YOLOv3" architecture, a streamlined deep learning detector that enables real-time, accurate identification of green mangoes in cluttered environments, a paper that has garnered 73 citations. Her work on tomato detection (66 citations) and green peach detection (24 citations) further advanced non-contact, efficient object recognition for harvesting robots. Notably, her research on a fast, non-contact ball detector (14 citations) addressed the high power consumption and memory footprint of traditional deep learning models on onboard devices. Through these innovations, Sun has significantly improved the viability of automated picking in agriculture, reducing computational overhead while maintaining robust performance under challenging field conditions.