Max Robotics — Global Service Robot Directory + US Certification

About

Yike Ma is pioneering the intersection of computer vision and agricultural robotics, with a focused mission to make automated fruit harvesting reliable and efficient. His core research spans occluded object recognition, multi-robot task allocation, and spherical image detection—all aimed at solving real-world challenges in precision agriculture. Ma’s most influential work, “An occluded cherry tomato recognition model based on improved YOLOv7” (12 citations), directly tackles the critical occlusion problem that hinders picking robots in natural environments. He further advances the field with a multi-layer model for small tomato picking robots (11 citations) and develops optimization frameworks for agricultural multi-robot systems, including an improved NSGA-II algorithm (10 citations) and a reinforcement learning-based approach (8 citations). Beyond agriculture, Ma contributes to fundamental computer vision with Gaussian Label Distribution Learning for spherical image object detection (8 citations), addressing regression challenges in applications from virtual reality to autonomous driving. His work demonstrates a rare ability to bridge theoretical innovation with practical deployment, making him a rising leader in intelligent agricultural robotics and perception systems.