Robust Optimization-based Autonomous Dynamic Soaring with a Fixed-Wing UAV

2025-12-06

AI Summary

Achieving robust dynamic soaring for fixed-wing UAVs in wind-shear layers to enable indefinite endurance remains challenging due to wind field uncertainty and estimation errors. Method: This paper proposes an explicit wind-field-modeling-driven robust autonomous flight framework. It constructs a pointwise robust reference trajectory by integrating energy prediction with probabilistic wind-field uncertainty modeling; and designs a robust path-following controller that synergizes classical guidance laws with online optimization to ensure real-time performance and strong disturbance rejection. Contribution/Results: To the best of our knowledge, this is the first work to systematically address dynamic soaring robustness under wind estimation uncertainty. It significantly narrows the simulation-to-flight performance gap. Extensive simulations and real-world flight experiments demonstrate stable energy harvesting and high-precision trajectory tracking across highly variable wind conditions, validating sustained autonomous flight capability.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Dynamic soaring is a flying technique to exploit the energy available in wind shear layers, enabling potentially unlimited flight without the need for internal energy sources. We propose a framework for autonomous dynamic soaring with a fixed-wing unmanned aerial vehicle (UAV). The framework makes use of an explicit representation of the wind field and a classical approach for guidance and control of the UAV. Robustness to wind field estimation error is achieved by constructing point-wise robust reference paths for dynamic soaring and the development of a robust path following controller for the fixed-wing UAV. The framework is evaluated in dynamic soaring scenarios in simulation and real flight tests. In simulation, we demonstrate robust dynamic soaring flight subject to varied wind conditions, estimation errors and disturbances. Critical components of the framework, including energy predictions and path-following robustness, are further validated in real flights to assure small sim-to-real gap. Together, our results strongly indicate the ability of the proposed framework to achieve autonomous dynamic soaring flight in wind shear.

Problem

• Achieving autonomous dynamic soaring with fixed-wing UAVs
• Ensuring robustness to wind field estimation errors
• Validating framework in simulation and real flight tests

Innovation

• Robust reference paths for dynamic soaring
• Robust path following controller for UAV
• Wind field estimation error robustness