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About

Qingyong Zhang is a robotics researcher whose work focuses on intelligent robotic systems for real-world applications, including firefighting, agriculture, elder care, and service robotics. His most-cited paper, "Intelligent Fire-fighting robot based on STM32" (2019, 11 citations), addresses the critical need for autonomous rescue robots in hazardous fire scenes, proposing a design that enhances safety and response efficiency. Zhang also contributes to agricultural automation through "Picking robot path planning based on improved ant colony algorithm" (2019, 3 citations), optimizing harvest efficiency with bio-inspired algorithms. In the domain of elder care, his "Design of Intelligent Escort Robot System Based on KCF Tracking Algorithm" (2020, 3 citations) leverages computer vision to support aging populations. Additionally, his "Voice-controlled Tea Pouring Robot Based on Machine Vision and Artificial Potential Field Method" (2020, 3 citations) integrates machine vision and obstacle avoidance for interactive service robotics. Zhang’s work demonstrates a commitment to bridging robotics with pressing societal needs, from disaster response to daily assistance, showcasing practical innovation with measurable impact.