Universität Bonn: Autonomous Intelligent Systems Group   Autonomous Intelligent Systems: NimbRo Picking

Amazon Robotics Challenge 2017

In the official practice run, our team reached the top score (150), followed by team IFL PiRo (KIT, Germany, 140), and team Nanyang (Nanyang Technological University, Singapore, 120). Teams could chose the practice task and the scores do not count towards the competition results. The score is promising, but there is still room for improvement.

Our system performed some practice runs. IMany items were sucessfully picked and placed, but there is still much room for improvement.

Our team arrived at the RoboCup venue in Nagoya, Japan, and started to assemble and set-up the developed robotic system.
This year, as final the Stow and Pick has been added, where the robotic system must pick the items that it stored before. Teams can design their own storage system, subject to space restrictions. The density of items in the tote and the storage systems has been increased. Maybe the most challenging aspect is that not all items are known in advance, but half of the items are introduced to the system only few minutes before the competition run.

NimbRo Picking system assembly NimbRo Picking ARC 2017 Robot System  

Our team NimbRo Picking is qualified for the Amazon Robotics Challenge 2017, which will taks place July 27th-30th in Nagoya, Japan.

The paper Max Schwarz, Anton Milan, Arul Selvam Periyasamy, and Sven Behnke:
RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter
has been accepted for International Journal of Robotics Research (IJRR), Sage Publications, to apprear 2017.

The abstract Max Schwarz and Sven Behnke:
Data-efficient Deep Learning for RGB-D Object Perception in Cluttered Bin Picking
has been accepted for the Warehouse Picking Automation Workshop (WPAW), IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017.

Amazon Picking Challenge 2016


The paper by Max Schwarz, Anton Milan, Christian Lenz, Aura Munoz, Arul Selvam Periyasamy, Michael Schreiber, Sebastian Schüller, and Sven Behnke: NimbRo Picking: Versatile Part Handling for Warehouse Automation has been accepted for the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 2017.
Finalist for Best Automation Paper Award.


We presented our approach to the APC tasks in the CASE Workshop on Automation for Warehouse Logistics, Fort Worth, Texas, USA.
[Presentation slides]



In the Picking task, our robot picked 10 of the 12 items from the shelf and placed them in the tote. It received 97 points, coming in third in the overall ranking, next to TU Delft and the Japanese Team PFN.

Chris NimbRo Team The most difficult object to suck on Results of the Picking task  Team NimbRo Picking 


Our team came in second in the Stowing task of the Amazon Picking Challenge, next only to the team of TU Delft. All but one object has been stowed. 

Stowing Results Max and Arul Anton and Aura


We used our practice run for the Stowing task. Our system was working quite well. NimbRo recived 123 points, followed by Duke (15 points) and MIT (10 points).


Our team made good progress in setting up the robot for the challenge. Here is a first video of picking from the tote.


Our team NimbRo Picking arrived at Leipziger Messe and is setting up the robot for the Amazon Picking Challenge.

NimbRo Picking Team NimbRo Picking robot


Our team NimbRo Picking is qualified for the Amazon Picking Challenge 2016, which will take place June 28th - July 3rd, 2016 at Leipziger Messe, colocated with RoboCup 2016. The challenge tasks consist of picking a large variety of objects from a shelf and placing them in a tote, and of picking unordered objects from a tote and stowing them in the shelf. 

Team NimbRo Picking     Amazon Picking Challenge 

Picking from ToteShelf with itemsPicking from Shelf

Related Projects

Universität Bonn, Institute for Computer Science, Departments: I, II, III, IV, V, VI; Team NimbRo; Robotics in Bonn