Adaptive morphing of wing and tail for stable, resilient, and energy-efficient flight of avian-informed drones

TL;DR

This paper introduces a robust control strategy and morphing techniques for avian-inspired drones, significantly improving their stability, energy efficiency, and adaptability in turbulent conditions through Bayesian optimization and bio-inspired design.

Contribution

It presents a new body-rate control method for drones with morphing wings and tails, and demonstrates energy efficiency gains via in-flight Bayesian optimization, mimicking avian flight.

Findings

Control method is robust against perturbations and actuator loss.

Morphing configurations improve energy efficiency up to 11.5%.

Drones exhibit flight patterns similar to birds at various speeds.

Abstract

Avian-informed drones feature morphing wing and tail surfaces, enhancing agility and adaptability in flight. Despite their large potential, realising their full capabilities remains challenging due to the lack of generalized control strategies accommodating their large degrees of freedom and cross-coupling effects between their control surfaces. Here we propose a new body-rate controller for avian-informed drones that uses all available actuators to control the motion of the drone. The method exhibits robustness against physical perturbations, turbulent airflow, and even loss of certain actuators mid-flight. Furthermore, wing and tail morphing is leveraged to enhance energy efficiency at 8m/s, 10m/s and 12m/s using in-flight Bayesian optimization. The resulting morphing configurations yield significant gains across all three speeds of up to 11.5% compared to non-morphing configurations and display a strong resemblance to avian flight at different speeds. This research lays the groundwork for the development of autonomous avian-informed drones that operate under diverse wind conditions, emphasizing the role of morphing in improving energy efficiency.