Abstract
The paper illustrates a system that endows an humanoid robot with the capability to mimic the motion of a human user in real time, serving as a basis for further gesture based human-robot interactions. The described approach uses the Microsoft Kinect as a low cost alternative to expensive motion capture devices.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Msrc-12 dataset. https://www.microsoft.com/en-us/download/details.aspx?id=52283
Ros kinetic. http://wiki.ros.org/kinetic
Semaphore flag signalling system. https://en.wikipedia.org/wiki/Flag_semaphore
Baron, G., Czekalski, P., Malicki, D., Tokarz, K.: Remote control of the artificial arm model using 3D hand tracking. In: 2013 International Symposium on Electrodynamic and Mechatronic Systems (SELM), pp. 9–10. IEEE (2013)
Chang, C.w., He, C.j., et al.: A kinect-based gesture command control method for human action imitations of humanoid robots. In: 2014 International Conference on Fuzzy Theory and Its Applications (iFUZZY 2014), pp. 208–211. IEEE (2014)
Chatzimilioudis, G., Cuzzocrea, A., Gunopulos, D., Mamoulis, N.: A novel distributed framework for optimizing query routing trees in wireless sensor networks via optimal operator placement. J. Comput. Syst. Sci. 79(3), 349–368 (2013)
Cuzzocrea, A.: Combining multidimensional user models and knowledge representation and management techniques for making web services knowledge-aware. Web Intell. Agent Syst. 4(3), 289–312 (2006)
Cuzzocrea, A., Bertino, E.: Privacy preserving OLAP over distributed XML data: a theoretically-sound secure-multiparty-computation approach. J. Comput. Syst. Sci. 77(6), 965–987 (2011)
Cuzzocrea, A., Moussa, R., Xu, G.: OLAP*: effectively and efficiently supporting parallel OLAP over big data. In: Cuzzocrea, A., Maabout, S. (eds.) MEDI 2013. LNCS, vol. 8216, pp. 38–49. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41366-7_4
Cuzzocrea, A., Russo, V.: Privacy preserving OLAP and OLAP security. In: Encyclopedia of Data Warehousing and Mining, 2nd edn (4 Volumes), pp. 1575–1581 (2009)
Filiatrault, S., Cretu, A.M.: Human arm motion imitation by a humanoid robot. In: 2014 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Proceedings, pp. 31–36. IEEE (2014)
Itauma, I.I., Kivrak, H., Kose, H.: Gesture imitation using machine learning techniques. In: 2012 20th Signal Processing and Communications Applications Conference (SIU), pp. 1–4. IEEE (2012)
Lau, M.C., Anderson, J., Baltes, J.: A sketch drawing humanoid robot using image-based visual servoing. Knowl. Eng. Rev. 34, e18 (2019)
Monje, C.A., de la Casa Díaz, S.M.: Modeling and control of humanoid robots. Int. J. Humanoid Rob. 16(6), 1902003:1–1902003:3 (2019)
Mukherjee, S., Paramkusam, D., Dwivedy, S.K.: Inverse kinematics of a NAO humanoid robot using kinect to track and imitate human motion. In: 2015 International Conference on Robotics, Automation, Control and Embedded Systems (RACE), pp. 1–7. IEEE (2015)
Pfitscher, M., Welfer, D., de Souza Leite Cuadros, M.A., Gamarra, D.F.T.: Activity gesture recognition on kinect sensor using convolutional neural networks and FastDTW for the MSRC-12 dataset. In: Abraham, A., Cherukuri, A.K., Melin, P., Gandhi, N. (eds.) ISDA 2018 2018. AISC, vol. 940, pp. 230–239. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-16657-1_21
Regier, P., Milioto, A., Karkowski, P., Stachniss, C., Bennewitz, M.: Classifying obstacles and exploiting knowledge about classes for efficient humanoid navigation. In: 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018, Beijing, China, 6–9 November 2018, pp. 820–826 (2018)
Saeedvand, S., Aghdasi, H.S., Baltes, J.: Robust multi-objective multi-humanoid robots task allocation based on novel hybrid metaheuristic algorithm. Appl. Intell. 49(12), 4097–4127 (2019). https://doi.org/10.1007/s10489-019-01475-8
Zabala, U., Rodriguez, I., Martínez-Otzeta, J.M., Lazkano, E.: Learning to gesticulate by observation using a deep generative approach. arXiv preprint arXiv:1909.01768 (2019)
Zhang, A., Ramirez-Alpizar, I.G., Giraud-Esclasse, K., Stasse, O., Harada, K.: Humanoid walking pattern generation based on model predictive control approximated with basis functions. Adv. Robot. 33(9), 454–468 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Augello, A., Ciulla, A., Cuzzocrea, A., Gaglio, S., Pilato, G., Vella, F. (2020). A Kinect-Based Gesture Acquisition and Reproduction System for Humanoid Robots. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12249. Springer, Cham. https://doi.org/10.1007/978-3-030-58799-4_69
Download citation
DOI: https://doi.org/10.1007/978-3-030-58799-4_69
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58798-7
Online ISBN: 978-3-030-58799-4
eBook Packages: Computer ScienceComputer Science (R0)