Mingbo Bi

North China University of Water Resources and Electric Power

Papers

Total Citations

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About

Mingbo Bi is a researcher at the forefront of agricultural robotics and computer vision, with a primary focus on intelligent perception systems for automated fruit harvesting. His most notable contribution is the development of the SCH-YOLO11s segmentation network, a novel deep learning architecture designed to solve the critical challenge of apple pose estimation. This work, published in 2025 and already accumulating 6 citations, addresses a fundamental bottleneck in robotic picking: accurately determining the three-dimensional orientation of apples by segmenting both the fruit and its calyx basin. By enabling robots to perceive fruit attitude with greater precision, Bi’s research directly advances the reliability and efficiency of autonomous harvesting systems. His approach integrates advanced object detection with fine-grained segmentation, pushing the boundaries of how agricultural robots interact with unstructured environments. As a researcher working at the intersection of artificial intelligence and precision agriculture, Bi’s contributions are helping to bridge the gap between laboratory algorithms and real-world field deployment, making him a key figure in the ongoing transformation of modern farming through intelligent automation.