π€ AI Summary
This work addresses the challenge of real-time trajectory planning and tracking for fixed-wing UAVs under wind disturbances, dynamical constraints, and time-varying curvature limits. We propose an online adaptive replanning method grounded in differential flatness. Leveraging the differential flatness property of coordinated flight dynamics, we formulate a compact state representation and generate dynamically feasible trajectories via nonlinear optimization; continuous in-flight replanning ensures adherence to evolving curvature constraints. To our knowledge, this is the first approach that tightly integrates differential-flat modeling with online curvature adaptation, significantly enhancing real-time responsiveness and trajectory fidelity for small-scale fixed-wing platforms operating in uncertain, high-wind environments. Comprehensive simulations and real-world flight experiments validate the methodβs capability to robustly synthesize and accurately track dynamically feasible trajectories under complex, time-varying constraints.
π Abstract
Efficient real-time trajectory planning and control for fixed-wing unmanned aerial vehicles is challenging due to their non-holonomic nature, complex dynamics, and the additional uncertainties introduced by unknown aerodynamic effects. In this paper, we present a fast and efficient real-time trajectory planning and control approach for fixed-wing unmanned aerial vehicles, leveraging the differential flatness property of fixed-wing aircraft in coordinated flight conditions to generate dynamically feasible trajectories. The approach provides the ability to continuously replan trajectories, which we show is useful to dynamically account for the curvature constraint as the aircraft advances along its path. Extensive simulations and real-world experiments validate our approach, showcasing its effectiveness in generating trajectories even in challenging conditions for small FW such as wind disturbances.