  We present RAPPIDS: a novel collision checking and planning algorithm for
multicopters that is capable of quickly finding local collision-free
trajectories given a single depth image from an onboard camera. The primary
contribution of this work is a new pyramid-based spatial partitioning method
that enables rapid collision detection between candidate trajectories and the
environment. By leveraging the efficiency of our collision checking method, we
shown how a local planning algorithm can be run at high rates on
computationally constrained hardware, evaluating thousands of candidate
trajectories in milliseconds. The performance of the algorithm is compared to
existing collision checking methods in simulation, showing our method to be
capable of evaluating orders of magnitude more trajectories per second.
Experimental results are presented showing a quadcopter quickly navigating a
previously unseen cluttered environment by running the algorithm on an
ODROID-XU4 at 30 Hz.
