Yihui Mao
Papers
1
Total Citations
7
H-Index
1
About
Yihui Mao is a researcher advancing the frontiers of safety-critical autonomous systems, with a primary focus on control theory, motion planning, and dynamic obstacle avoidance. His most-cited work, "Safety-Critical Planning and Control for Dynamic Obstacle Avoidance Using Control Barrier Functions" (2025, 7 citations), addresses a fundamental challenge in robotics and autonomous navigation: ensuring real-time safety in unpredictable environments. Mao’s key contribution lies in integrating Control Barrier Functions (CBFs) with optimization-based trajectory planning, moving beyond static distance-based formulations to handle moving obstacles effectively. This work bridges the gap between theoretical safety guarantees and practical deployment, offering a robust framework for autonomous vehicles, drones, and mobile robots. By tackling the complexity of dynamic environments, Mao’s research has immediate implications for safer autonomous systems in transportation and industrial applications. His growing citation record reflects the timeliness and utility of his contributions. For students and researchers in control and robotics, Mao’s work exemplifies how rigorous mathematical tools can be translated into real-world safety solutions, making him a rising voice in the field of safety-critical planning.
Research Focus
Key Achievements
Top Papers
- 1