Jinyu Xu

Huazhong University of Science and Technology

Papers

Total Citations

H-Index

About

Jinyu Xu is a robotics researcher whose work focuses on advancing intelligent manipulation and autonomous assembly for industrial applications, particularly within the 3C (computer, communication, consumer electronics) manufacturing sector. His key research areas include variable impedance control, multi-robot coordination, and vision-based robotic assembly. Xu’s most significant contributions lie in developing adaptive control frameworks that integrate machine learning and computer vision to enhance robotic precision and flexibility. Notably, his 2020 paper on "Variable Impedance Control of Manipulator Based on DQN" pioneered the use of deep reinforcement learning to dynamically adjust robot stiffness and damping during tasks, enabling safer and more efficient human-robot interaction. His 2019 work on "Multi-robot Collaborative Assembly Research for 3C Manufacturing" demonstrated a practical solution for server motherboard assembly, addressing real-world industrial challenges. Additionally, his vision-based position/impedance control framework eliminated the need for tedious manual target pose detection, streamlining robotic assembly processes. While his citation counts (3–4 per paper) reflect a focused, early-career impact, Xu’s work is notable for its direct relevance to Industry 4.0, bridging the gap between theoretical control algorithms and deployable manufacturing solutions.