Soft Aerial Robots: The Development of Adaptive, Multi‐Functional and Multi‐Terrain Aerial Robots
P. H. Nguyen, Salua Hamaza, Pakpong Chirarattananon, Y. Chen, M. Kovac · Advanced Intelligent Systems · 2025
Classical aerial robots have demonstrated precise control and high speeds through the use of highly optimized rigid body structures.However, when compared to their biological flying counterparts, they still struggle to match performance parameters in energy efficiency, multi-functionality, multi-terrain accessibility, scalability (to micro-scale), agility, close contact interaction, robustness, and maneuverability in cluttered environments.The recent emergence of soft aerial robotics has seen an increased interest in the utilization of smart and functional materials to develop aerial robots with innovative and morphologically adaptive structures.Through the interpretation and study of biological flyers, soft aerial robots leverage their morphological features, to exploit dynamic and biomechanical effects to achieve better aerodynamic performance, interact safely with unknown and cluttered environments, sensing itself and its surroundings better, and expand their range of capabilities.Taking another bold step towards autonomous operation in real-world environments.We organized this special issue to highlight top-tier work of leading researchers in the field of bio-inspired, reconfigurable, adaptive, and soft aerial robotics, in order continue the ongoing conversation about the current state of the art, as well as technical and conceptual obstacles, and to examine the difficulties and prospects for the future of soft aerial robotics.In this issue, we observe several research thrusts currently in focus.For example, De Petris et al. demonstrate how morphological compliance, embedded sensing, and collision resilience converge in Morphy.A quadcopter developed with sensorized elastic joints that withstand high-speed impacts, provide real-time angle deflection feedback, and compress to squeeze through narrow openings.[1] Abazari et al. investigated optimal compliance in MAVs for collision resilience.Their tests showed that softer propeller guards led to more elastic collisions without improving energy dissipation, while softening the inner frame enhanced energy damping and extended collision time, reducing impact accelerations.[2] Kubota et al. explored a learning-based wind classification method using multiple strain sensors that detect wing deformation in flexible wings on a hummingbird-mimetic mechanism.The setup highlighted high accuracies in distinguishing wind direction under varying flow conditions.This highlights the potential of wing strain sensing for enabling quick responses to flow disturbances in aerial robots.[3] Shape morphing to extend the flight envelope of aerial robots was another pivotal focus.Tang et al. developed PairTilt, a quadcopter with a two pair of tiltable, coupled rotors that minimizes www.advancedsciencenews.