Combining Planning and Learning of Behavior Trees for Robotic Assembly

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@InProceedings{Styrud:2022:ICRA,

• author = "Jonathan Styrud and Matteo Iovino and Mikael Norrloef and Marten Bjoerkman and Christian Smith",
• booktitle = "2022 International Conference on Robotics and Automation (ICRA)",
• title = "Combining Planning and Learning of Behavior Trees for Robotic Assembly",
• year = "2022",
• pages = "11511--11517",
• abstract = "Industrial robots can solve tasks in controlled environments, but modern applications require robots able to operate also in unpredictable surroundings. An increasingly popular reactive policy architecture in robotics is Behavior Trees (BTs) but as other architectures, programming time drives cost and limits flexibility. The two main branches of algorithms to generate policies automatically, automated planning and machine learning, both have their own drawbacks and have not previously been combined for generation of BTs. We propose a method for creating BTs by combining these branches, inserting the result of an automated planner into the population of a Genetic Programming algorithm. Experiments confirm that the proposed method performs well on a variety of robotic assembly problems and outperforms the base methods used separately. We also show that this high level learning of Behavior Trees can be transferred to a real system without further training.",
• keywords = "genetic algorithms, genetic programming, Robotic assembly, Training, Machine learning algorithms, Service robots, Sociology, Planning, Behavior Trees, Assembly",
• DOI = "doi:10.1109/ICRA46639.2022.9812086",
• month = may,
• notes = "Also known as \cite{9812086}",

}

Genetic Programming entries for Jonathan Styrud Matteo Iovino Mikael Norrloef Marten Bjoerkman Christian Smith

Citations