An Autonomous and Flexible Robotic Framework for Logistics Applications

In this paper, we present an intelligent and flexible framework for autonomous pick-and-place tasks in previously unknown scenarios. It includes modules for object recognition, environment modeling, motion planning and collision avoidance, as well as sophisticated error handling and a task superviso...

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Bibliographic Details
Published inJournal of intelligent & robotic systems Vol. 93; no. 3-4; pp. 419 - 431
Main Authors Wahrmann, Daniel, Hildebrandt, Arne-Christoph, Schuetz, Christoph, Wittmann, Robert, Rixen, Daniel
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.03.2019
Springer
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Collision avoidance
Control
Electrical Engineering
Engineering
Harvesting
Logistics
Machine vision
Mechanical Engineering
Mechatronics
Motion planning
Object recognition
Pick and place tasks
Robotics
Supply chain management software
Motion planning
Computer vision
Pick-and-place
Control
Industrial automation
Grasping
Industry 4.0
Autonomous manufacturing
Software framework
Autonomous robotics
Robotics
Industrial robotics
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Summary:In this paper, we present an intelligent and flexible framework for autonomous pick-and-place tasks in previously unknown scenarios. It includes modules for object recognition, environment modeling, motion planning and collision avoidance, as well as sophisticated error handling and a task supervisor. The framework combines state-of-the-art algorithms and was validated during the first phase of the European Robotics Challenge in which it obtained first place in a field of 39 international contestants. We discuss our results and the potential application of our framework to real industrial tasks. Furthermore, we validate our approach with an application on a real harvesting manipulator. To inspire other teams participating in the challenge and as a tool for new researchers in the field, we release it as open source.
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-017-0746-8