  In this work, we present a system that enables delivery drones to
autonomously navigate and deliver packages at various locations around a house
according to the desire of the recipient and without the need for any external
markers as currently used. This development is motivated by recent advancements
in deep learning that can potentially supplant the specialized markers
presently used by delivery drones for identifying sites at which to deliver
packages. The proposed system is more natural in that it takes instruction on
where to deliver the package as input, similar to the instructions provided to
human couriers. First, we propose a semantic image segmentation-based
descending location estimator that enables the drone to find a safe spot around
the house at which it can descend from higher altitudes. Following this, we
propose a strategy for visually routing the drone from the descent location to
a specific site at which it is to deliver the package, such as the front door.
We extensively evaluate this approach in a simulated environment and
demonstrate that with our system, a delivery drone can deliver a package to the
front door and also to other specified locations around a house. Relative to a
frontier exploration-based strategy, drones using the proposed system found and
reached the front doors of the 20 test houses 161% faster.
