Aerodynamic Prior-Free Trajectory Generation and Tracking Control for Tail-Sitter UAVs
Original title:Aerodynamic Prior-Free Coordinated Trajectory Generation and Tracking Control for a Tail-Sitter UAV
Tail-sitter UAVs typically require labor-intensive wind tunnel tests or airframe-specific aerodynamic identification to ensure stable transitions across the full flight envelope. Researchers from Sun Yat-sen University introduce an aerodynamic prior-free framework that decouples planning from tracking. The method leverages coordinated-flight phi-theory for analytic differential flatness in planning, paired with model predictive control for online aerodynamic parameter estimation during tracking. The approach demonstrated robust real-world tracking across transition regimes, and the implementation has been released on GitHub.
Why it's worth reading
It eliminates the need for cumbersome aerodynamic identification campaigns in tail-sitter UAVs by decoupling planning and adaptive tracking, backed by successful real-world flight validation and open source code.