Abstract
When it comes to physical collaboration between humans and robots, robots currently have a shortcoming: their ability to observe and adapt to human dynamics is limited. This leads to inefficient collaboration and unergonomic interaction. In this work, we combine a dynamic phase state system (PSS) based on a network of stable heteroclinic channels (SHC) with Compliant Movement Primitives (CMP). The combination of PSS and CMP enables intuitive human interaction in tasks where humans and robots physically cooperate. The capabilities of the control system were demonstrated in simulations involving helping a humanoid bipedal robot Talos stand up from a squat position by pulling on its hands.
Keywords
- Humanoids
- Compliant movement primitives
- Phase state system
This work was supported by Slovenian Research Agency grant N2-0153.
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Brecelj, T., Petrič, T.: Angular dependency of the zero moment point. In: Zeghloul, S., Laribi, M.A., Sandoval, J. (eds.) Advances in Service and Industrial Robotics, pp. 135–144. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75259-0-15
Deimel, R.: Reactive interaction through body motion and the phase-state-machine. In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019
Denisa, M., Gams, A., Ude, A., Petric, T.: Learning compliant movement primitives through demonstration and statistical generalization. IEEE/ASME Trans. Mechatron. (2016). https://doi.org/10.1109/TMECH.2015.2510165
Denisa, M., Petrič, T., Asfour, T., Ude, A.: Synthesizing compliant reaching movements by searching a database of example trajectories. In: International Conference on Humanoid Robots, pp. 540–546 (2013)
Horchler, A.D., Daltorio, K.A., Chiel, H.J., Quinn, R.D.: Designing responsive pattern generators: stable heteroclinic channel cycles for modeling and control. Bioinspir. Biom. 10(2), 1–16 (2015). https://doi.org/10.1088/1748-3190/10/2/026001
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)
Laurent, G., Stopfer, M., Friedrich, R.W., Rabinovich, M.I., Volkovskii, A., Abarbanel, H.D.: Odor encoding as an active, dynamical process: experiments, computation, and theory. Ann. Rev. Neurosci. 24(1), 263–297 (2001). https://doi.org/10.1146/annurev.neuro.24.1.263
Miškovič, L., Koprivšek Leskovar, R., Gams, A., Petrič, T.: Optimizing end-effector force during the sit-stand task on the TALOS humanoid bipedal robot. In: Žemva, A., Trost, A. (eds.) Proceedings of the 30th International Electrotechnical and Computer Science Conference ERK 2021, pp. 175–178. Slovenska sekcija IEEE: Fakulteta za elektrotehniko, Ljubljana (2021)
Petrič, T., Gams, A., Colasanto, L., Ijspeert, A.J., Ude, A.: Accelerated sensorimotor learning of compliant movement primitives. IEEE Trans. Robot. 34(6), 1636–1642 (2018). https://doi.org/10.1109/TRO.2018.2861921
Rabinovich, M.I., Huerta, R., Varona, P., Afraimovich, V.S.: Transient cognitive dynamics, metastability, and decision making. PLoS Comput. Biol. 4(5), 25–30 (2008). https://doi.org/10.1371/journal.pcbi.1000072
Saeedvand, S., Jafari, M., Aghdasi, H.S., Baltes, J.: A comprehensive survey on humanoid robot development. Knowl. Eng. Rev. 34, e20 (2019). https://doi.org/10.1017/S0269888919000158
Stasse, O., et al.: TALOS: A new humanoid research platform targeted for industrial applications. In: IEEE-RAS International Conference on Humanoid Robots, pp. 689–695 (2017). https://doi.org/10.1109/HUMANOIDS.2017.8246947
Ude, A., Nemec, B., Petrič, T., Morimoto, J.: Orientation in cartesian space dynamic movement primitives. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 2997–3004, May 2014
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Petrič, T., Žlajpah, L. (2022). Phase State System for Generating Interactive Behaviors for Humanoid Robots. In: Müller, A., Brandstötter, M. (eds) Advances in Service and Industrial Robotics. RAAD 2022. Mechanisms and Machine Science, vol 120. Springer, Cham. https://doi.org/10.1007/978-3-031-04870-8_58
Download citation
DOI: https://doi.org/10.1007/978-3-031-04870-8_58
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-04869-2
Online ISBN: 978-3-031-04870-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)