Differential Flatness-based Fast Trajectory Planning for Fixed-wing Unmanned Aerial Vehicles

TL;DR

This paper introduces a differential flatness-based trajectory optimization method for fixed-wing UAVs that significantly reduces computation time and ensures physical feasibility, enabling rapid trajectory planning in complex environments.

Contribution

The paper develops a novel, efficient trajectory optimization approach using differential flatness and polynomial parameterization, avoiding complex dynamics constraints for fixed-wing UAVs.

Findings

Achieves sub-second trajectory computation times.

Outperforms existing methods in efficiency by orders of magnitude.

Successfully plans trajectories in obstacle-rich environments.

Abstract

Due to the strong nonlinearity and nonholonomic dynamics, despite the various general trajectory optimization methods presented, few of them can guarantee efficient computation and physical feasibility for relatively complicated fixed-wing UAV dynamics. Aiming at this issue, this paper investigates a differential flatness-based trajectory optimization method for fixed-wing UAVs (DFTO-FW). The customized trajectory representation is presented through differential flat characteristics analysis and polynomial parameterization, eliminating equality constraints to avoid the heavy computational burdens of solving complex dynamics. Through the design of integral performance costs and derivation of analytical gradients, the original trajectory optimization is transcribed into a lightweight, unconstrained, gradient-analytical optimization with linear time complexity to improve efficiency further. The simulation experiments illustrate the superior efficiency of the DFTO-FW, which takes sub-second CPU time (on a personal desktop) against other competitors by orders of magnitude to generate fixed-wing UAV trajectories in randomly generated obstacle environments.