Four aspects of building robotic systems: lessons from the Amazon Picking Challenge 2015

Abstract

We describe the winning entry to the Amazon Picking Challenge 2015. 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 versus integration, generality versus assumptions, computation versus embodiment, and planning versus 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 2015 challenge entries along each of the spectra.