Fan Ding
Papers
1
Total Citations
2
H-Index
1
About
Fan Ding is a robotics researcher whose work focuses on the intersection of safe control, motion planning, and autonomous systems, with a particular emphasis on mobile robotic manipulators. Their key contributions lie in developing configuration-aware safety frameworks that address the fundamental challenge of spatial awareness in robotic collision avoidance. In their highly regarded 2022 paper, Ding introduced a novel approach using Control Barrier Functions (CBFs) to design safe control laws for mobile robotic arms, tackling the complex problem of how a robot's spatial structure affects its ability to navigate and operate safely in dynamic environments. This work, which has garnered citations from the growing safe robotics community, represents a significant step forward in enabling robots to reason about their own geometry during real-time control. Ding's research bridges theoretical control theory with practical robotic applications, offering elegant mathematical solutions to real-world safety challenges. Their work is particularly valuable for students and researchers interested in the intersection of formal safety guarantees and autonomous mobile manipulation, demonstrating how rigorous mathematical frameworks can be applied to create more capable and trustworthy robotic systems.
Research Focus
Key Achievements
Top Papers
- 1