Abstract
The number of industrial robots used worldwide has been continuously increasing. In almost all cases the application program has the form of a text based source code, which has inherent drawbacks (in terms of complexity and ease of development) when compared to the graphical approaches seen in general purpose software engineering. These graphical programming approaches have not been developed, having industrial robots in mind. In this paper a behavior trees based approach for creating and representing source code for robotic applications is proposed. The software architecture and an experimental implementation of the developed programming method is presented and a validation using a common assembly task is shown.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
1. Sonya Alexandrova, Zachary Tatlock, and Maya Cakmak. Roboflow: A flow-based visual programming language for mobile manipulation tasks. IEEE International Conference on Robotics and Automation (ICRA), pages 5537–5544, May 2015.
2. M. Colledanchise, A. Marzinotto, D. V. Dimarogonas, and P. Oegren. The advantages of using behavior trees in mult-robot systems. In Proceedings of ISR 2016: 47st International Symposium on Robotics, pages 1–8, June 2016.
3. IFR Statistical Department and Carsten Heer. World robotics 2016 - industrial robots post a new sales record in 2015 a rise of 8 percent. 2016.
4. Staffan Ekvall and Danica Kragic. Robot learning from demonstration: A task-level planning approach. volume 5, pages 223–234. InTech, 2008.
5. K. R. Guerin, C. Lea, C. Paxton, and G. D. Hager. A framework for end-user instruction of a robot assistant for manufacturing. In 2015 IEEE International Conference on Robotics and Automation (ICRA), pages 6167–6174, May 2015.
6. B. Iske and U. Ruckert. A methodology for behaviour design of autonomous systems. In Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on, volume 1, pages 539–544 vol.1, 2001.
7. Damian Isla. Handling complexity in the halo 2 ai. In Game developers conference, volume 12, 2005.
8. Chong-U Lim. An a.i. player for defcon: An evolutionary approach using behavior trees. Master’s thesis, Department of Computing Imperial College London, 2009.
9. T. Lozano-Perez. Robot programming. Proceedings of the IEEE, 71(7):821–841, July 1983.
10. Pedro Neto, J. Norberto Pires, and Ant´onio Paulo Moreira. High-level programming and control for industrial robotics: using a hand-held accelerometer-based input device for gesture and posture recognition. CoRR, abs/1309.2093, 2013.
11. J. Palsberg and C. B. Jay. The essence of the visitor pattern. In Computer Software and Applications Conference, 1998. COMPSAC ’98. Proceedings. The Twenty-Second Annual International, pages 9–15, Aug 1998.
12. Zengxi Pan, Joseph Polden, Nathan Larkin, Stephen Van Duin, and John Norrish. Recent progress on programming methods for industrial robots. Robotics and Computer-Integrated Manufacturing, 28(2):87 – 94, 2012.
13. M. R. Pedersen, L. Nalpantidis, A. Bobick, and V. Krger. On the integration of hardware-abstracted robot skills for use in industrial scenarios. Aalborg University Copenhagen, 2014.
14. Alexander Perzylo, Nikhil Somani, Stefan Profanter, Markus Rickert, and Alois Knoll. Toward efficient robot teach-in and semantic process descriptions for small lot sizes. In Robotics: Science and Systems (RSS), Workshop on Combining AI Reasoning and Cognitive Science with Robotics, Rome, Italy, pages 1–7, 2015.
15. F. Rovida and V. Krger. Design and development of a software architecture for autonomous mobile manipulators in industrial environments. In Industrial Technology (ICIT), 2015 IEEE International Conference on, pages 3288–3295, March 2015.
16. C. Schou, J.S. Damgaard, S. Bogh, and O. Madsen. Human-robot interface for instructing industrial tasks using kinesthetic teaching. In Robotics (ISR), 2013 44th International Symposium on, pages 1–6, Oct 2013.
17. U Thomas, Gerd Hirzinger, Bernhard Rumpe, Christoph Schulze, and Andreas Wortmann. A new skill based robot programming language using uml/p statecharts. IEEE International Conference on Robotics and Automation (ICRA), pages 461–466, May 2013.
18. Jonathan Tremblay. Understanding and evaluating behaviour trees. McGill University, Modelling, Simulation and Design Lab, Tech. Rep, 2012.
19. Wikipedia. Behavior tree (artificial intelligence, robotics and control). https://en.wikipedia.org/wiki/Behavior_tree_(artificial_intelligence,_robotics_and_control). [Online; accessed 05-July-2016].
20. Stefan Zei. Manipulation skill for robotic assembly. Master’s thesis, Technische Universitt Darmstadt, June 2014.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer-Verlag GmbH Deutschland
About this paper
Cite this paper
Csiszar, A., Hoppe, M., Khader, S.A., Verl, A. (2017). Behavior Trees for Task-Level Programming of Industrial Robots. In: Schüppstuhl, T., Franke, J., Tracht, K. (eds) Tagungsband des 2. Kongresses Montage Handhabung Industrieroboter. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54441-9_18
Download citation
DOI: https://doi.org/10.1007/978-3-662-54441-9_18
Published:
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-54440-2
Online ISBN: 978-3-662-54441-9
eBook Packages: Computer Science and Engineering (German Language)