Low-Cost Differential Flatness Identification for Trajectory Planning and Tracking of Small Fixed-Wing UAVs in Dense Environments

Differential-flatness-based trajectory planning and tracking is a promising approach for small fixed-wing UAVs traversing dense obstacle environments. However, there is a gap between numerical simulations and experiments due to the lack of effective identification methods for differential flatness. In this paper, we develop a practical 3-dimensional differential flatness of fixed-wing UAVs and propose a corresponding identification method. First, a signal-to-thrust model is introduced into differential flatness to directly work with general-purpose flight control units (FCUs) and benefit the identification. Second, a low-cost parameter identification method for differential flatness is proposed without requiring expensive or laborious pre-measurements. Third, the methods to apply them to high-quality trajectory planning and tracking are presented. High-fidelity semi-physical simulations demonstrate that our methods can navigate a small fixed-wing UAV through dense environments, and comparison tests show the superiority of the proposed identification method.