Team Delft’s robot winner of the Amazon Picking Challenge 2016

C. Hernandez Corbato*, Mukunda Bharatheesha, Wilson Ko, Hans Gaiser, Jethro Tan, Kanter van Deurzen, Maarten de Vries, Bas Van Mil, Jeff van Egmond, Ruben Burger, Mihai Morariu, Jihong Ju, X. Gerrmann, Ronald Ensing, Jan Van Frankenhuyzen, Martijn Wisse

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

67 Citations (Scopus)

Abstract

This paper describes Team Delft’s robot, which won the Amazon Picking Challenge 2016, including both the Picking and the Stowing competitions. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. Team Delft’s robot is based on an industrial robot arm, 3D cameras and a customized gripper. The robot’s software uses ROS to integrate off-the-shelf components and modules developed specifically for the competition, implementing Deep Learning and other AI techniques for object recognition and pose estimation, grasp planning and motion planning. This paper describes the main components in the system, and discusses its performance and results at the Amazon Picking Challenge 2016 finals.

Original languageEnglish
Title of host publicationRoboCup 2016: Robot World Cup XX
EditorsS Behnke, R Sheh, S Sariel, DD Lee
Place of PublicationCham, Switzerland
PublisherSpringer
Pages613-624
ISBN (Electronic) 978-3-319-68792-6
ISBN (Print)9783319687919
DOIs
Publication statusPublished - 2017
EventRoboCup 2016: 20th Annual RoboCup International Symposium - Leipzig, Germany
Duration: 30 Jun 20164 Jul 2016

Publication series

NameLecture Notes in Computer Science (Subserie Lecture Notes in Artificial Intelligence)
PublisherSpringer International Publishing AG
Volume9776
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceRoboCup 2016: 20th Annual RoboCup International Symposium
Country/TerritoryGermany
CityLeipzig
Period30/06/164/07/16

Bibliographical note

Champion Paper

Keywords

  • Deep learning
  • Grasping
  • Motion planning
  • Robotic system
  • Warehouse automation

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