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Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing

1,462 views · Published 2 March 2018 · 2:52 · Indexed 5 October 2026

Channel: nimbro · 2018 · Science & Technology

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The video illustrates the paper 
Max Schwarz, Christian Lenz, German Martin Garcia, Seongyong Koo, Arul Selvam Periyasamy, Michael Schreiber, and Sven Behnke: "Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing"
IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018. 

http://www.ais.uni-bonn.de/papers/ICRA_2018_Schwarz_ARC.pdf

Abstract:
Robotic picking from cluttered bins is a demanding
task, for which Amazon Robotics holds challenges. The
2017 Amazon Robotics Challenge (ARC) required stowing items
into a storage system, picking specific items, and packing
them into boxes. In this paper, we describe the entry of
team NimbRo Picking. Our deep object perception pipeline
can be quickly and efficiently adapted to new items using
a custom turntable capture system and transfer learning. It
produces high-quality item segments, on which grasp poses are
found. A planning component coordinates manipulation actions
between two robot arms, minimizing execution time. The system
has been demonstrated successfully at ARC, where our team
reached second places in both the picking task and the final
stow-and-pick task. We also evaluate individual components.

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