当柔软让你变得强硬：一个受节肢动物外骨骼启发的碰撞弹性四轴飞行器
When Being Soft Makes You Tough: A Collision-Resilient Quadcopter Inspired by Arthropods' Exoskeletons
摘要：
飞行机器人通常相当脆弱，在面临碰撞风险时需要保护外壳，而高复杂性和有效载荷减少是碰撞弹性飞行机器人经常出现的问题。受节肢动物外骨骼的启发，我们设计了一种简单、开源、易于制造的半刚性结构，具有柔软的关节，可以承受高速冲击。通过外骨骼，保护壳成为机器人主结构的一部分，从而最大限度地减少其有效载荷能力的损失。我们的设计易于使用廉价的组件（例如竹串）和消费级3D打印机进行构建和定制。其结果是CogniFly，这是一种低于250 g的自主四轴飞行器，可以在高达7 m/s的速度下经受多次碰撞。除了它的碰撞弹性，CogniFly很容易使用Python或Buzz编程，携带传感器，使它能够飞行大约。17分钟，无需GPS或外部动作捕捉系统，具有足够的计算能力来运行深度神经网络模型，旨在促进与自动电池更换系统的集成。这种结构成为高风险活动的理想平台（例如在混乱的环境中飞行或强化学习训练），大大降低了损坏自身硬件或环境的风险。源代码、3D文件、说明和视频可通过该项目的网站（https：//www.example.com）获得。thecognifly.github.io
英文摘要：
Flying robots are usually rather delicate and require protective enclosures when facing the risk of collision, while high complexity and reduced payload are recurrent problems with collision-resilient flying robots. Inspired by arthropods' exoskeletons, we design a simple, open source, easily manufactured, semi-rigid structure with soft joints that can withstand high-velocity impacts. With an exoskeleton, the protective shell becomes part of the main robot structure, thereby minimizing its loss in payload capacity. Our design is simple to build and customize using cheap components (e.g. bamboo skewers) and consumer-grade 3D printers. The result is CogniFly, a sub-250g autonomous quadcopter that survives multiple collisions at speeds up to 7m/s. In addition to its collision-resiliency, CogniFly is easy to program using Python or Buzz, carries sensors that allow it to fly for approx. 17min without the need of GPS or an external motion capture system, has enough computing power to run deep neural network models on-board and was designed to facilitate integration with an automated battery swapping system. This structure becomes an ideal platform for high-risk activities (such as flying in a cluttered environment or reinforcement learning training) by dramatically reducing the risks of damaging its own hardware or the environment. Source code, 3D files, instructions and videos are available through the project's website (https://thecognifly.github.io).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
