Mingqu Fan

Shandong University of Science and Technology

Papers

Total Citations

H-Index

About

Mingqu Fan is a robotics researcher whose work focuses on advancing locomotion and manipulation in legged and dual-arm robotic systems. His key research areas include gait generation for quadruped robots and coordinated control for dual-arm manipulators. Fan’s most notable contribution is a novel continuous free gait generation method for quadruped robots, enabling stable walking over rough terrains characterized by uneven ground and obstacles. This work, published in 2019, has garnered 19 citations and addresses a fundamental challenge in field robotics: robust, adaptive locomotion without predefined footfall patterns. In earlier work, Fan developed a master-slave force hybrid coordinated motion control method for dual-arm robots using model predictive control (MPC). By integrating six-axis force sensors at the arm endpoints, his 2016 paper (9 citations) improved real-time coordination and force regulation, critical for tasks like assembly or object manipulation. Fan’s research bridges theoretical control algorithms with practical robotic hardware, contributing to more autonomous and versatile robots for unstructured environments. His work is particularly relevant for students and researchers interested in legged locomotion, multi-arm coordination, and model-based control in robotics.