Maode Yan
Papers
3
Total Citations
30
H-Index
2
About
Maode Yan is a leading researcher in intelligent transportation systems and robotic control, with a focus on vehicle platooning and rehabilitation robotics. His most impactful work, published in 2020, addresses the complex challenge of coordinating heterogeneous vehicles in platoons under real-world constraints. In this highly cited paper (26 citations), Yan proposes a distributed model predictive control (DMPC) scheme that simultaneously handles multiple vehicle constraints—such as acceleration limits and spacing policies—while accounting for communication delays between vehicles. This contribution is critical for advancing autonomous convoy systems, improving traffic flow, and enhancing safety in connected vehicle networks. Yan also explores the intersection of cloud robotics and wireless communication, developing a Lyapunov optimization-based MAC protocol for hierarchical cloud-robot systems to manage diverse hardware and quality-of-service requirements. Additionally, his work in rehabilitation robotics includes a repetitive control strategy for periodic walking training in gait rehabilitation robots, demonstrating his versatility in applying control theory to both automotive and medical domains. Yan’s research, bridging theoretical control methods with practical implementation challenges, continues to influence the development of safer, more efficient autonomous systems.
Research Focus
Key Achievements
Top Papers
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