Ming Hung Lin
Papers
1
Total Citations
15
H-Index
1
About
Ming Hung Lin is a robotics researcher whose work centers on the control and coordination of non-holonomic mobile robot systems, with a particular focus on formation control and obstacle avoidance. His most cited paper, "Examining the performance of Laguerre-based and nonlinear predictive control models for wheeled mobile robots when facing obstacles" (2024, 15 citations), introduces a virtual structure formation control strategy that enables teams of rotating, non-holonomic robots to navigate barrier environments. This work addresses the critical challenge of calculating individual robot paths while maintaining cohesive group formation, contributing to the broader field of multi-agent robotic systems. Though early in his citation impact, Lin's research has implications for autonomous navigation in constrained environments, such as warehouse logistics or search-and-rescue operations. His approach combines predictive control models with practical implementation considerations, bridging theoretical control theory and real-world robotic applications. As a researcher focused on the intersection of nonlinear control and mobile robotics, Lin's work continues to explore how non-holonomic constraints can be effectively managed in dynamic, obstacle-rich settings.
Research Focus
Key Achievements
Top Papers
- 1