My primary research interest lies in developing intelligent and reliable robotic systems
that better understand and express human intentions to reduce labor costs in real-world applications.
To achieve this goal, my recent work focuses on leveraging trajectory optimization and generative models
to create adaptable robotic solutions.
I'm particularly interested in bridging high-level human instructions with physical implementations through text-to-motion frameworks
and enhanced scene understanding capabilities.
Pulications & Projects
Learning LiDAR-Based Dynamic Obstacle Avoidance via Time-to-Collision Supervision
This project develops a multi-UAV system integrating LiDAR and vision sensing for
autonomous navigation in complex environments while maintaining precise formation control.
Auto filmer: Autonomous aerial videography under human interaction
