Zhanghao Qu

Northwest A&F University, Northwest Institute of Mechanical and Electrical Engineering

Papers

Total Citations

H-Index

About

Zhanghao Qu is a researcher advancing the intersection of computer vision and robotics for precision agriculture. His work focuses on developing intelligent perception and mechanical systems to automate key tasks in fruit harvesting and crop monitoring. Qu’s most cited paper, “A Diameter Measurement Method of Red Jujubes Trunk Based on Improved PSPNet” (2022, 19 citations), introduces a deep learning approach for trunk segmentation and diameter estimation, directly improving the effectiveness of vibration harvesting robots. This contribution addresses a critical bottleneck in automated jujube harvesting by enabling robots to accurately target and grasp tree trunks. In another significant work, “Optimal Design of Agricultural Mobile Robot Suspension System Based on NSGA-III and TOPSIS” (2023, 10 citations), Qu tackles the underexplored challenge of vehicle stability in agricultural robots. By applying multi-objective optimization algorithms, he provides a framework for designing suspension systems that enhance robot mobility on uneven terrain. His research is notable for bridging the gap between traditional automotive suspension design and the unique structural demands of agricultural robotics. With a growing citation record, Qu is establishing himself as a key contributor to the engineering of robust, intelligent agricultural machinery.