Abstract—We describe the winning entry to the Amazon
Picking Challenge. From the experience of building this system
and competing in the Amazon Picking Challenge, we derive
several conclusions: 1) We suggest to characterize robotic system
building along four key aspects, each of them spanning a
spectrum of solutions—modularity vs. integration, generality
vs. assumptions, computation vs. embodiment, and planning
vs. feedback. 2) To understand which region of each spectrum
most adequately addresses which robotic problem, we must
explore the full spectrum of possible approaches. To achieve this,
our community should agree on key aspects that characterize the
solution space of robotic systems. 3) For manipulation problems
in unstructured environments, certain regions of each spectrum
match the problem most adequately, and should be exploited
further. This is supported by the fact that our solution deviated
from the majority of the other challenge entries along each of
the spectra.