Jun‐Ming Xu
Papers
1
Total Citations
5
H-Index
1
About
Jun-Ming Xu is a robotics researcher whose work centers on the locomotion and control of legged robots, with a particular focus on quadrupedal systems. Their most notable contribution is the development of a trot gait parameters planning system for parallel quadruped robots, which integrates a virtual model controller with a fuzzy neural network. This innovative approach enables more adaptive and stable gait generation, addressing key challenges in dynamic walking and terrain adaptability. While their research is still emerging, Xu’s work has already garnered early citations, reflecting its relevance to the growing field of bio-inspired robotics and intelligent control. By combining model-based control with machine learning techniques, Xu is helping to bridge the gap between theoretical control systems and practical robotic locomotion. Their research holds promise for applications in search-and-rescue, exploration, and autonomous navigation, where robust and efficient quadrupedal movement is critical. As a researcher, Xu is contributing to the next generation of agile, intelligent robots capable of operating in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1