Flight through Narrow Gaps with Morphing-Wing Drones

2026-03-12

AI Summary

This study addresses the challenge that fixed-wing unmanned aerial vehicles (UAVs) struggle to navigate through narrow gaps narrower than their wingspan and are prone to instability at low speeds with high angles of attack. Inspired by avian flight, this work proposes a morphing-wing UAV system capable of actively folding its wings mid-flight to traverse confined openings. The key innovation lies in the first integration of a variable-wing airframe with a nonlinear model predictive control (NMPC) framework that adapts in real time to dynamic cost functions and constraints. By cohesively combining aerodynamic modeling, longitudinal dynamics, and optimized trajectory generation, the system achieves precise and stable gap traversal. Experimental results on a 130-gram prototype demonstrate an average altitude error of only 5 cm while flying through gaps at 5–7 m/s, with wing-folding timing dynamically adjusted based on proximity thresholds.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Intelligent Robots: Motion and Path Planning
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

The size of a narrow gap traversable by a fixed-wing drone is limited by its wingspan. Inspired by birds, here, we enable the traversal of a gap of sub-wingspan width and height using a morphing-wing drone capable of temporarily sweeping in its wings mid-flight. This maneuver poses control challenges due to sudden lift loss during gap-passage at low flight speeds and the need for precisely timed wing-sweep actuation ahead of the gap. To address these challenges, we first develop an aerodynamic model for general wing-sweep morphing drone flight including low flight speeds and post-stall angles of attack. We integrate longitudinal drone dynamics into an optimal reference trajectory generation and Nonlinear Model Predictive Control framework with runtime adaptive costs and constraints. Validated on a 130 g wing-sweep-morphing drone, our method achieves an average altitude error of 5 cm during narrow-gap passage at forward speeds between 5 and 7 m/s, whilst enforcing fully swept wings near the gap across variable threshold distances. Trajectory analysis shows that the drone can compensate for lift loss during gap-passage by accelerating and pitching upwards ahead of the gap to an extent that differs between reference trajectory optimization objectives. We show that our strategy also allows for accurate gap passage on hardware whilst maintaining a constant forward flight speed reference and near-constant altitude.

Problem

• narrow-gap traversal
• morphing-wing drone
• lift loss
• wing-sweep actuation
• low-speed flight

Innovation

• morphing-wing drone
• narrow-gap traversal
• nonlinear model predictive control
• aerodynamic modeling
• optimal trajectory generation