Publication
Behavior Tree as a Decision Planning Algorithm for Industrial Robot
Martina Hutter-Mironovova; Benjamin Blumhofer; Christopher Schneider; Achim Wagner
In: Leonard Barolli (Hrsg.). Advances on P2P, Parallel, Grid, Cloud and Internet Computing. Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2024), Cham, Pages 385-394, ISBN 978-3-031-76462-2, Springer Nature Switzerland, 2025.
Abstract
In traditional industrial settings, robot execution planning is typically governed by pre-programmed instructions, with cell logic predominantly managed by PLC (Programmable Logic Controller) systems. However, the rapid advancements in artificial intelligence have unlocked new possibilities, enabling the deployment of robots in previously unautomated sectors. Enhanced machine vision, advanced data processing, and increased adaptability to dynamic environments are now within reach. These developments necessitate a re-evaluation of conventional approaches to robot and cell programming. This paper explores the implementation of behavior trees as an alternative execution planning algorithm, specifically applied to an industrial YASKAWA robot, demonstrating their potential to optimize performance and flexibility in complex industrial applications in dynamic environment.