Towards Endowing Collaborative Robots with Fast Learning for Minimizing Tutors’ Demonstrations: What and When to Do?
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Programming by demonstration allows non-experts in robot programming to train the robots in an intuitive manner. However, this learning paradigm requires multiple demonstrations of the same task, which can be time-consuming and annoying for the human tutor. To overcome this limitation, we propose a fast learning system – based on neural dynamics – that permits collaborative robots to memorize sequential information from single task demonstrations by a human-tutor. Important, the learning system allows not only to memorize long sequences of sub-goals in a task but also the time interval between them. We implement this learning system in Sawyer (a collaborative robot from Rethink Robotics) and test it in a construction task, where the robot observes several human-tutors with different preferences on the sequential order to perform the task and different behavioral time scales. After learning, memory recall (of what and when to do a sub-task) allows the robot to instruct inexperienced human workers, in a particular human-centered task scenario.
KeywordsIndustrial robotics Assembly tasks Learning from demonstration Sequence order and timing Rapid learning Dynamic Neural Fields
- 6.Ferreira, F., Erlhagen, W., Bicho, E.: A dynamic field model of ordinal and timing properties of sequential events. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2011). https://doi.org/10.1007/978-3-642-21738-8_42Google Scholar
- 8.Ferreira, F., Erlhagen, W., Sousa, E., Louro, L., Bicho, E.: Learning a musical sequence by observation: a robotics implementation of a dynamic neural field model. In: IEEE ICDL-EPIROB 2014 - 4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, pp. 157–162 (2014). https://doi.org/10.1109/DEVLRN.2014.6982973
- 10.Orendt, E.M., Fichtner, M., Henrich, D.: Robot programming by non-experts: intuitiveness and robustness of one-shot robot programming. In: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 192–199. IEEE (2016). https://doi.org/10.1109/ROMAN.2016.7745110
- 11.Papanastasiou, S., Kousi, N., Karagiannis, P., Gkournelos, C., Papavasileiou, A., Dimoulas, K., Baris, K., Koukas, S., Michalos, G., Makris, S.: Towards seamless human robot collaboration: integrating multimodal interaction. Int. J. Adv. Manuf. Technol. 1–17 (2019). https://doi.org/10.1007/s00170-019-03790-3CrossRefGoogle Scholar
- 12.Robotics, R.: Sawyer collaborative robot (2018). http://www.rethinkrobotics.com/sawyer/
- 13.Sandamirskaya, Y., Zibner, S.K.U., Schneegans, S., Schöner, G.: Using dynamic field theory to extend the embodiment stance toward higher cognition. New Ideas Psychol. 31(3), 322–339 (2013). https://doi.org/10.1016/j.newideapsych.2013.01.002CrossRefGoogle Scholar
- 17.Wojtak, W., Ferreira, F., Louro, L., Bicho, E., Erlhagen, W.: Towards temporal cognition for robots: a neurodynamics approach. In: 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017, pp. 407–412 (2018). https://doi.org/10.1109/DEVLRN.2017.8329836