An Autonomous and Flexible Robotic Framework for Logistics Applications
| Autor: | Christoph Schuetz, Arne-Christoph Hildebrandt, Daniel Wahrmann, Robert Wittmann, Daniel J. Rixen |
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| Přispěvatelé: | Lehrstuhl für Angewandte Mechanik |
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Supervisor business.industry Computer science Mechanical Engineering lola Cognitive neuroscience of visual object recognition Robotics 02 engineering and technology Phase (combat) Industrial and Manufacturing Engineering Field (computer science) Task (project management) ddc 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Human–computer interaction Artificial intelligence Motion planning Electrical and Electronic Engineering business Software Collision avoidance |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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