Abstract
Progressive automation aims at quick and easy programming of repetitive tasks by means of kinesthetic demonstration from an operator. In this paper we address the general case, where the operator demonstrates a task involving motion of both the robot’s wrist position and its orientation, so that the robot progressively transitions from manual into autonomous operation based on the agreement level between consecutive demonstrations. Utilizing unit quaternions, we propose a method that combines dynamic movement primitives for encoding the task space motion with variable stiffness control for continuous role allocation, enabling an operator to easily program task by demonstration. We verify experimentally that a pick and place task with changes in the position and the orientation can be programmed with the proposed method in less than a minute.
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
Similar content being viewed by others
Notes
- 1.
Video demonstration of the experiment: https://youtu.be/rgv95sprPG0.
References
Billard, A.G., Calinon, S., Dillmann, R.: Learning from humans. In: Springer Handbook of Robotics, pp. 1995–2014. Springer (2016)
Tykal, M., Montebelli, A., Kyrki, V.: Incrementally assisted kinesthetic teaching for programming by demonstration. In: ACM/IEEE International Conference on Human-Robot Interaction, April 2016, pp. 205–212 (2016)
Saveriano, M., An, S.I., Lee, D.: Incremental kinesthetic teaching of end-effector and null-space motion primitives. In: Proceedings - IEEE International Conference on Robotics and Automation, June 2015, pp. 3570–3575 (2015)
Lee, D., Ott, C.: Incremental kinesthetic teaching of motion primitives using the motion refinement tube. Auton. Robot. 31, 115–131 (2011)
Dimeas, F., Fotiadis, F., Papageorgiou, D., Sidiropoulos, A., Doulgeri, Z.: Towards progressive automation of repetitive tasks through physical human-robot interaction. In: Human-Friendly Robotics. Springer Proceedings in Advanced Robotics (2018)
Schmidt, J., Niemann, H.: Using quaternions for parametrizing 3-d rotations in unconstrained nonlinear optimization. In: VMV 2001 (VMV), pp. 399–406 (2001)
Ijspeert, A.J., Nakanishi, J., Hoffmann, H., Pastor, P., Schaal, S.: Dynamical movement primitives: learning attractor models for motor behaviors. Neural Comput. 25(2), 328–373 (2013)
Ude, A., Gams, A., Asfour, T., Morimoto, J.: Task-specific generalization of discrete and periodic dynamic movement primitives. IEEE Trans. Robot. 26(5), 800–815 (2010)
Schaal, S., Atkeson, C.: Constructive incremental learning from only local information. Neural Comput. 10(8), 2047–2084 (1998)
Kulvicius, T., Ning, K., Tamosiunaite, M., Wörgötter, F.: Joining movement sequences: modified dynamic movement primitives for robotics applications exemplified on handwriting. IEEE Trans. Robot. 28(1), 145–157 (2012)
Acknowledgements
This work is funded by “Supporting researchers with emphasis on young researchers” grant no. MIS 5004792 from the “Development of Human Resources, Education and Lifelong Learning” national program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Dimeas, F., Doulgeri, Z. (2019). Progressive Automation of Repetitive Tasks Involving both Translation and Rotation. In: Aspragathos, N., Koustoumpardis, P., Moulianitis, V. (eds) Advances in Service and Industrial Robotics. RAAD 2018. Mechanisms and Machine Science, vol 67. Springer, Cham. https://doi.org/10.1007/978-3-030-00232-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-00232-9_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00231-2
Online ISBN: 978-3-030-00232-9
eBook Packages: EngineeringEngineering (R0)