Abstract
Learning from demonstrations (LfD) is receiving more attention recently as an important modality for teaching robots and other agents new skills by untrained users. A successful LfD system must tackle several problems including the decision about what and whom to imitate but, ultimately, it needs to reproduce the skill it learned solving the how to imitate problem. One promising approach to solving this problem is using Gaussian Mixture Modeling and Gaussian Mixture Regression for reproduction. Most available systems that utilize this approach rely on kinesthetic teaching or require the attachment of special markers to measure joint angles of the demonstrator. This bypasses the correspondence problem which is accounting for the difference in the kinematic model of the demonstrator and the learner. This paper presents a closed-form analytic solution to the correspondence problem for an upper-body of a humanoid robot that is general enough to be applicable to many available humanoid robots and reports the application of the method to a pose copying task executed by a NAO robot using Kinect recorded data of human demonstrations.
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
Preview
Unable to display preview. Download preview PDF.
References
Aleotti, J., Caselli, S.: Grasp programming by demonstration: A task-based quality measure. In: Robot and Human Interactive Communication, RO-MAN 2008, pp. 383–388 (2008)
Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Robotics and Autonomous Systems 57(5), 1–15 (2009)
Abbeel, P., Coates, A., Ng, A.Y.: Autonomous Helicopter Aerobatics through Apprenticeship Learning. The International Journal of Robotics Research 29(13), 1608–1639 (2010)
Nehaniv, C., Dautenhahn, K.: Mapping between dissimilar bodies: Affordances and the algebraic foundations of imitation. In: Demiris, J., Birk, A. (eds.) Proceedings European Workshop on Learning Robots 1998, EWLR-7 (1998)
Mohammad, Y., Nishida, T., Okada, S.: Unsupervised simultaneous learning of gestures, actions and their associations for human-robot interaction. In: Intelligent Robots and Systems, IROS, pp. 2537–2544. IEEE (2009)
Mohammad, Y., Nishida, T.: Learning interaction protocols using augmented baysian networks applied to guided navigation. In: Intelligent Robots and Systems, IROS, pp. 4119–4126. IEEE (2010)
Mohammad, Y., Nishida, T.: Fluid imitation: Discovering what to imitate. International Journal of Social Robotics 4(4), 369–382 (2012)
Calinon, S., Guenter, F., Billard, A.: On learning, representing, and generalizing a task in a humanoid robot. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics 37(2), 286–298 (2007)
Nehaniv, C., Dautenhahn, K.: Mapping between dissimilar bodies: A ordances and the algebraic foundations of imitation. In: EWLR 1998, pp. 64–72 (1998)
Asfour, T., Dillmann, R.: Human-like motion of a humanoid robot arm based on a closed-form solution of the inverse kinematics problem. In: Intelligent Robots and Systems, IROS, pp. 1407–1412. IEEE (2003)
Pitt, J., Hildenbrand, D., Stelzer, M., Koch, A.: Inverse kinematics of a humanoid robot based on conformal geometric algebra using optimized code generation. In: IEEE Humanoids 2008, pp. 681–686 (2008)
Nunez, J.V., Briseno, A., Rodriguez, D.A., Ibarra, J.M., Rodriguez, V.M.: Explicit analytic solution for inverse l.kinematics of bioloid humanoid robot. In: IEEE-Brazilian Robotics Symposium and Latin American Robotics Symposium, SBR-LARS, pp. 33–38 (2012)
Ali, M.A., Park, H.A., Lee, C.G.: Closed-form inverse kinematic joint solution for humanoid robots. In: Intelligent Robots and Systems, IROS, pp. 704–709. IEEE (2010)
Tee, K.P., Yan, R., Chua, Y., Huang, Z.: Singularity-robust modular inverse kinematics for robotic gesture imitation. In: 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO, pp. 920–925. IEEE (2010)
Zannatha, J.I., Limón, R.C.: Forward and inverse kinematics for a small-sized humanoid robot. In: International Conference on Electrical, Communications, and Computers, CONIELECOMP 2009, pp. 111–118. IEEE (2009)
Wang, J., Li, Y.: Inverse kinematics analysis for the arm of a mobile humanoid robot based on the closed-loop algorithm. In: International Conference on Information and Automation, ICIA 2009, pp. 516–521. IEEE (2009)
Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Robotics and Autonomous Systems 57(5), 469–483 (2009)
Paul, R.P., Shimano, B., Mayer, G.E.: Kinematic control equations for simple manipulators. IEEE Transactions on Systems, Man, and Cybernetics 11, 449–455 (1981)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Mohammad, Y., Nishida, T. (2013). Tackling the Correspondence Problem. In: Yoshida, T., Kou, G., Skowron, A., Cao, J., Hacid, H., Zhong, N. (eds) Active Media Technology. AMT 2013. Lecture Notes in Computer Science, vol 8210. Springer, Cham. https://doi.org/10.1007/978-3-319-02750-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-02750-0_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02749-4
Online ISBN: 978-3-319-02750-0
eBook Packages: Computer ScienceComputer Science (R0)