  Quadrotors can provide services such as infrastructure inspection and
search-and-rescue, which require operating autonomously in cluttered
environments. Autonomy is typically achieved with receding-horizon planning,
where a short plan is executed while a new one is computed, because sensors
receive limited information at any time. To ensure safety and prevent robot
loss, plans must be verified as collision free despite uncertainty (e.g,
tracking error). Existing spline-based planners dilate obstacles uniformly to
compensate for uncertainty, which can be conservative. On the other hand,
reachability-based planners can include trajectory-dependent uncertainty as a
function of the planned trajectory. This work applies Reachability-based
Trajectory Design (RTD) to plan quadrotor trajectories that are safe despite
trajectory-dependent tracking error. This is achieved by using zonotopes in a
novel way for online planning. Simulations show aggressive flight up to 5 m/s
with zero crashes in 500 cluttered, randomized environments.
