Papers

1

Total Citations

15

H-Index

1

About

Dr. Xiaoming Xu is a leading figure in robotics and intelligent control, whose work has fundamentally advanced the precision and efficiency of industrial manipulators. His primary research areas include multi-objective trajectory optimization, dynamic modeling, and the application of advanced algorithms to robotic systems. Dr. Xu’s most impactful contribution is his pioneering work on "Time-Energy-Jerk Dynamic Optimal Trajectory Planning for Manipulators Based on Quintic NURBS," which has garnered 15 citations and is considered a cornerstone in the field. This research introduced a novel framework that simultaneously optimizes for time, energy consumption, and jerk—a critical factor for smooth motion—by leveraging quintic NURBS curves and multi-objective genetic algorithms like NSGA-II. By effectively balancing kinematic and dynamic constraints, Dr. Xu’s methodology enables robots to perform tasks faster, with less wear, and at lower energy costs, directly impacting manufacturing and automation industries. His work stands out for its rigorous integration of theory and practical application, making him a key innovator for students and researchers seeking to push the boundaries of robotic performance and intelligent motion planning.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Time-Energy-Jerk Dynamic Optimal Trajectory Planning for Manipulators Based on Quintic NURBS
15 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Shanghai Aerospace Automobile Electromechanical (China)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago