Dual-modal trajectory planning method for compound-wing UAV leveraging differential flatness in urban environments

The rise of the low-altitude economy highlights the importance of compound-wing UAVs. However, achieving seamless and optimal trajectories across different flight modes remains a significant challenge due to inherent high-order discontinuities during mode transitions. To address this limitation, the Spatial-Temporal Adaptive Dual-modal Trajectory Planning (STA-DTP) method for compound-wing UAVs is proposed. By leveraging the differential flatness characteristics of the compound-wing UAV's dual-modal dynamics, a Dynamic collocation-point-based Minimum Control Effort Polynomial (D-MINCO) trajectory parameterization model is developed. Its polynomial design ensures high-order continuity and allows for decoupled spatial-temporal representation of dual-modal trajectories, significantly reducing optimization complexity. An adaptive collocation-point decision mechanism for dual-modal transition is designed to address the dependence of trajectory optimality on transition timing. Integrated with an Anytime framework, this mechanism facilitates the real-time generation of feasible dual-modal flight trajectories. Transition collocation points are adaptively assigned based on conflicts between trajectory states and dynamic constraints. Under available computational resources, trajectory optimality is progressively enhanced through the densification collocation-point strategy. Compared with typical trajectory planning algorithms (i.e., STA-DTP, SFC-SCP, and GPOPS-II) using fixed transition-point strategies, simulation results demonstrate that the proposed method achieves improvements of 1–2 orders of magnitude in planning efficiency and reduces trajectory flight durations as well. Consequently, this work provides an efficient and optimal framework for trajectory planning of compound-wing UAVs in urban environments.