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

  • Clemens Eppner
  • Sebastian Höfer
  • Rico Jonschkowski
  • Roberto Martín-Martín
  • Arne Sieverling
  • Vincent Wall
  • Oliver Brock
Article
Part of the following topical collections:
  1. Special Issue on Robotics: Science and Systems 2016

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.

Keywords

Robotic systems Amazon Picking Challenge Warehouse automation Mobile manipulation 

Notes

Acknowledgements

We would like to thank Barrett Technology for their support and our team members Raphael Deimel, Roman Kolbert, Gabriel Le Roux, and Wolf Schaarschmidt, who helped creating the winning system.

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Robotics and Biology LaboratoryBerlinGermany

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