Wind-Aware Optimal Trajectory Planning for Efficient Gliding of Fixed-Wing Aerial Systems

2026-05-15

AI Summary

This work addresses the challenge of effectively managing glide energy for small fixed-wing UAVs under wind disturbances and obstacle constraints, where conventional approaches rely on reactive control and require meticulous parameter tuning. The authors elevate energy regulation to the planning level by proposing a nonlinear multi-objective trajectory planning method that, for the first time, achieves wind-aware energy-balanced gliding directly at the trajectory level. Integrating empirical sink polar curves with a net rate-of-climb model, the approach generates C³-continuous glide trajectories using Bernstein polynomials and maps them to control inputs via differential flatness. Cruise segments are initialized with Dubins paths, enabling online replanning and obstacle avoidance. Simulations and real-world flight tests demonstrate that the method effectively stabilizes sink rate, airspeed, and glide ratio in complex environments, confirming its reliability and practicality.

Abstract

Gliding offers small fixed-wing UAVs extended endurance and silent operation but requires accurate energy management, especially under wind disturbances and obstacle constraints. Traditional Total Energy Control Systems based controllers regulate the trade between potential and kinetic energy reactively, often requiring fine-tuning and trim-conditions knowledge. In this work, we shift the regulation to the planning level and present a nonlinear, multi-cost trajectory planner for small UAV gliders. The method generates $\mathcal{C}^3$ continuous trajectories based on Bernstein polynomials, mapped into control commands through differential flatness, and re-planned online to match experimentally derived sink polar curves. A simulated netto variometer is integrated into the optimization to estimate air mass motion, constraining the glide to energy-balanced states. Consecutive gliding trajectories are linked by cruising segments computed through trajectories initialized on Dubins path-based waypoints, enabling hybrid missions that combine powered and unpowered flight. The approach is validated in CFD simulations and real-world experiments with a fixed-wing platform, showing reliable stabilization of sink rate, airspeed, and glide ratio under wind gusts and in presence of obstacles.

Problem

• gliding
• wind disturbance
• energy management
• fixed-wing UAV
• obstacle constraints

Innovation

• trajectory planning
• energy-aware gliding
• Bernstein polynomials
• differential flatness
• netto variometer