A Framework for Learning Behavior Trees in Collaborative Robotic Applications
A Framework for Learning Behavior Trees in Collaborative Robotic Applications
- Neue Suche nach: Iovino, Matteo
- Neue Suche nach: Styrud, Jonathan
- Neue Suche nach: Falco, Pietro
- Neue Suche nach: Smith, Christian
- Neue Suche nach: Iovino, Matteo
- Neue Suche nach: Styrud, Jonathan
- Neue Suche nach: Falco, Pietro
- Neue Suche nach: Smith, Christian
In modern industrial collaborative robotic applications, it is desirable to create robot programs automatically,intuitively, and time-efficiently. Moreover, robots need to becontrolled by reactive policies to face the unpredictability ofthe environment they operate in. In this paper we proposea framework that combines a method that learns BehaviorTrees (BTs) from demonstration with a method that evolvesthem with Genetic Programming (GP) for collaborative roboticapplications. The main contribution of this paper is to show thatby combining the two learning methods we obtain a method thatallows non-expert users to semi-automatically, time-efficiently,and interactively generate BTs. We validate the framework witha series of manipulation experiments. The BT is fully learnt insimulation and then transferred to a real collaborative robot. ; Submitted to the IEEE for possible publication QC 20230525
Dokumentinformationen
A Framework for Learning Behavior Trees in Collaborative Robotic Applications
Paper
Elektronische Ressource
Englisch
| DDC: | 629 |
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