Abstract
Several approaches exist for learning and control of robot behaviors in physical human-robot interaction (PHRI) scenarios. One of these is the approach based on virtual guides which actively helps to guide the user. Such a system enables guiding users towards preferred movement directions or prevents them to enter into a prohibited zone. Despite being shown that such a framework works well in physical contact with humans, the efficient interaction with the environment is still limited. Within the virtual guide framework, the environment is considered as a physical guide, for example, a table is a plane that prevents the robot to penetrate through. To mitigate these limits we introduce and evaluate the means of autonomous path adaptation through interaction with physical guides, which essentially means merging virtual and physical guides. The virtual guide framework was extended by introducing an algorithm which partially modifies the virtual guides online. The path updates are now based on the interactive force measurements and essentially improves the virtual guides to match them with the actual physical guides.
This work was supported by Slovenian Research Agency grant N2-0130.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Billard, A., Calinon, S., Dillmann, R., Schaal, S.: Robot Programming by Demonstration, pp. 1371–1394. Springer, Heidelberg (2008)
Gams, A., Petrič, T., Do, M., Nemec, B., Morimoto, J., Asfour, T., Ude, A.: Adaptation and coaching of periodic motion primitives through physical and visual interaction. Robot. Auton. Syst. (2015). https://doi.org/10.1016/j.robot.2015.09.011
Gruebler, A., Berenz, V., Suzuki, K.: Coaching robot behavior using continuous physiological affective feedback. In: 2011 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Bled, Slovenia, pp. 466–471(2011)
Lee, D., Ott, C.: Incremental kinesthetic teaching of motion primitives using the motion refinement tube. Auton. Robots 31(2–3), 115–131 (2011)
Nicolescu, M.N., Mataric, M.J.: Natural methods for robot task learning: instructive demonstrations, generalization and practice. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 241–248 (2003)
Ott, C., Mukherjee, R., Nakamura, Y.: Unified impedance and admittance control. In: Proceedings - IEEE International Conference on Robotics and Automation, pp. 554–561 (2010)
Petrič, T., Žlajpah, L.: On-line adaption of virtual guides through physical interaction. In: Berns, K., Görges, D. (eds.) Advances in Service and Industrial Robotics, pp. 293–300. Springer, Cham (2020)
Ranatunga, I., Lewis, F.L., Popa, D.O., Tousif, S.M.: Adaptive admittance control for human-robot interaction using model reference design and adaptive inverse filtering. IEEE Trans. Control Syst. Technol. 25(1), 278–285 (2017). https://doi.org/10.1109/TCST.2016.2523901
Restrepo, S.S., Raiola, G., Chevalier, P., Lamy, X., Sidobre, D.: Iterative virtual guides programming for human-robot comanipulation. In: 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), pp. 219–226. IEEE, July 2017
Riley, M., Ude, A., Atkeson, C., Cheng, G.: Coaching: an approach to efficiently and intuitively create humanoid robot behaviors. In: 2006 6th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Genoa, Italy, pp. 567–574 (2006)
Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G.: Robotics - Modelling. Planning and Control. Springer, London (2009)
Žlajpah, L., Petrič, T.: Unified virtual guides framework for path tracking tasks. Robotica 1–17. https://doi.org/10.1017/S0263574719000973
Žlajpah, L., Petrič, T.: Virtual guides for redundant robots using admittance control for path tracking tasks. In: Aspragathos, N.A., Koustoumpardis, P.N., Moulianitis, V.C. (eds.) Advances in Service and Industrial Robotics: Proceedings of the 27th International Conference on Robotics in Alpe-Adria Danube Region (RAAD 2018), pp. 13–23. Springer (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Petrič, T., Žlajpah, L. (2020). Combining Virtual and Physical Guides for Autonomous In-Contact Path Adaptation. In: Zeghloul, S., Laribi, M., Sandoval Arevalo, J. (eds) Advances in Service and Industrial Robotics. RAAD 2020. Mechanisms and Machine Science, vol 84. Springer, Cham. https://doi.org/10.1007/978-3-030-48989-2_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-48989-2_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48988-5
Online ISBN: 978-3-030-48989-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)