  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).
