Papers
12
Total Citations
85
H-Index
5
About
Mingxin Yuan is a robotics and computational intelligence researcher whose work sits at the intersection of bio-inspired optimization algorithms and autonomous robot navigation. Over more than a decade of sustained research, Yuan has made significant contributions to robot motion and path planning by drawing innovative analogies from immunology and swarm intelligence. His most influential work introduced hybrid frameworks combining ant colony optimization with artificial immune network theory — most notably the AC-INA algorithm — to tackle complex motion planning challenges in dynamic environments, earning over 20 citations. Yuan extended these immunological principles across multiple domains, developing novel immune network strategies for path planning in complicated environments and multi-robot task allocation systems. His research also encompasses neural network-based camera calibration for intelligent spaces, self-tuning PID controllers using radial basis function networks for service robot trajectory tracking, and multi-objective immune optimization for ship welding robots. More recently, Yuan has addressed the challenging problem of online multi-robot coordination in dynamic environments through secondary immune response-inspired algorithms. With a cumulative body of work spanning foundational algorithm design to practical industrial applications, Yuan's research has meaningfully advanced the field of intelligent autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5APF-guided adaptive immune network algorithm for robot path planning5 citations · 2009
- 6
- 7
- 8
- 9
- 10