The increasing use of drones in human-centric applications highlights the need for designs that can survive collisions and recover rapidly, minimizing risks to both humans and the environment. We present HoLoArm, a quadrotor with compliant arms inspired by the nodus structure of dragonfly wings. This design provides natural flexibility and resilience while preserving flight stability, which is further reinforced by the integration of a Reinforcement Learning (RL) control policy that enhances both recovery and hovering performance. Experimental results demonstrate that HoLoArm can passively deform in any direction, including axial one, and recover within 0.3-0.6 s depending on the direction and level of the impact. The drone can survive collisions at speeds up to 7.6 m/s and carry a 540 g payload while maintaining stable flight. This work contributes to the morphological design of soft aerial robots with high agility and reliable safety, enabling operation in cluttered and human shared environments, and lays the groundwork for future fully soft drones that integrate compliant structures with intelligent control.

翻译：随着无人机在以人为中心的应用中日益普及，亟需能够承受碰撞并快速恢复的设计方案，以最大程度降低对人和环境的风险。本文提出HoLoArm——一种受蜻蜓翅痣结构启发的柔性机臂四旋翼无人机。该设计在提供天然柔韧性与抗冲击能力的同时，保持了飞行稳定性，并通过引入强化学习（RL）控制策略进一步增强了恢复与悬停性能。实验结果表明，HoLoArm能够在任意方向（包括轴向）被动变形，并根据冲击方向与强度在0.3-0.6秒内恢复。该无人机可承受最高7.6米/秒的碰撞速度，并在携带540克有效载荷时保持稳定飞行。本工作为兼具高敏捷性与可靠安全性的软体空中机器人形态设计做出贡献，使其能够在杂乱及人机共融环境中运行，并为未来将柔性结构与智能控制相集成的全软体无人机奠定基础。