Yuheng Lin
Papers
1
Total Citations
12
H-Index
1
About
Yuheng Lin is a rising leader in aerial robotics, specializing in the control and coordination of multi-robot systems in challenging, cluttered environments. His core research focuses on nonlinear model predictive control (MPC) and the integration of neural networks to predict complex aerodynamic effects, particularly the downwash interference that plagues quadrotor swarms during close-proximity flight. In his highly cited 2023 work, Lin pioneered a novel framework that uses a neural network to model the otherwise intractable, nonlinear downwash dynamics, enabling quadrotors to maintain tight formation without destabilizing each other. This contribution directly addresses a critical bottleneck in swarm robotics—allowing teams of drones to navigate narrow passages safely and efficiently. With 12 citations on this foundational paper alone, Lin’s work is rapidly gaining traction for its practical impact on autonomous aerial operations. His achievements represent a significant step toward robust, real-world deployment of dense aerial swarms for search-and-rescue, infrastructure inspection, and environmental monitoring.
Research Focus
Key Achievements
Top Papers
- 1