Yongfeng Gao
Papers
1
Total Citations
3
H-Index
1
About
Yongfeng Gao is a researcher advancing the field of robotics and autonomous systems, with a primary focus on safety-critical control, multi-robot coordination, and motion planning. His most-cited work, "Safety-critical model predictive control for trajectory tracking and obstacle avoidance of wheeled mobile robot formations," tackles the fundamental challenge of enabling robot teams to navigate confined spaces while maintaining strict safety guarantees. By developing an online model predictive control framework, Gao overcomes the limitations of traditional offline optimization methods, allowing wheeled mobile robot formations to dynamically track trajectories and avoid obstacles in real time. This contribution is pivotal for applications in warehouse logistics, search-and-rescue, and autonomous transportation. With 3 citations since its 2025 publication, his work is already drawing attention for its practical relevance in deploying safe, scalable multi-robot systems. Gao’s research bridges the gap between theoretical control theory and real-world robotic deployment, making him a notable emerging voice in the safety-critical robotics community.
Research Focus
Key Achievements
Top Papers
- 1