Mingfang Chen

Kunming University of Science and Technology

Papers

6

Total Citations

46

H-Index

4

About

Mingfang Chen is a robotics researcher specializing in legged locomotion, parallel mechanisms, and motion control, with a particular focus on the design and optimization of quadruped robots and parallel manipulators. His work addresses fundamental engineering challenges in robotic systems, most notably the persistent problem of high leg inertia in electrically driven quadruped robots. By repositioning knee motors within the robot's body and developing novel single-leg architectures, Chen has made meaningful advances in improving stability, reducing mechanical complexity, and enhancing control precision in walking robots. His contributions extend beyond structural design into trajectory planning, where he has developed bionic foot-end trajectories adaptable to diverse terrains and gaits by intelligently combining Cartesian and joint-space planning strategies. His research on central pattern generator-based control for parallel-legged quadrupeds further demonstrates his breadth across both hardware and software domains. Chen has also made notable contributions to parallel manipulator research, exploring asymmetric 4-DOF configurations and advancing kinematic calibration techniques for improved pose accuracy. His published body of work has accumulated over 45 citations, reflecting growing recognition within the robotics community. His research offers valuable insights for engineers and students working at the intersection of biomimetic design, mechanism theory, and autonomous locomotion systems.

Research Focus

Key Achievements

4
H-Index
6
Papers
46
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Single‐Leg Structural Design and Foot Trajectory Planning for a Novel Bioinspired Quadruped Robot
13 citations · 2021
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Kunming University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago