Abstract
Redundant robots have received increased attention during the last decades, since they provide solutions to problems investigated for years in the robotic community, e.g. task-space tracking, obstacle avoidance etc. However, robot redundancy may arise problems of kinematic control, since robot joint motion is not uniquely determined. In this paper, a biomimetic approach is proposed for solving the problem of redundancy resolution. First, the kinematics of the human upper limb while performing random arm motion are investigated and modeled. The dependencies among the human joint angles are described using a Bayesian network. Then, an objective function, built using this model, is used in a closed-loop inverse kinematic algorithm for a redundant robot arm. Using this algorithm, the robot arm end-effector can be positioned in the three dimensional (3D) space using human-like joint configurations. Through real experiments using an anthropomorphic robot arm, it is proved that the proposed algorithm is computationally fast, while it results to human-like configurations compared to previously proposed inverse kinematics algorithms. The latter makes the proposed algorithm a strong candidate for applications where anthropomorphism is required, e.g. in humanoids or generally in cases where robotic arms interact with humans.
Similar content being viewed by others
References
Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 6, 716–723.
Artemiadis, P. K., & Kyriakopoulos, K. J. (2009). A bio-inspired filtering framework for the EMG-based control of robots. In Proc. of 17th Mediterranean conference on control and automation.
Asfour, T., & Dillmann, R. (2003). Human-like motion of a humanoid robot arm based on a closed-form solution of the inverse kinematics problem. In Proc. of IEEE/RSJ int. conf. on intelligent robots and systems, 2, 1407–1412.
Bentivegna, D., Atkeson, C., & Cheng, G. (2004). Learning tasks from observation and practice. Robotics and Autonomous Systems, 47, 163–169.
Billard, A., & Mataric, M. J. (2001). Learning human arm movements by imitation: evaluation of a biologically inspired connectionist architecture. Robotics and Autonomous Systems, 37, 145–160.
Billard, A. G., Calinon, S., & Guenter, F. (2006). Discriminative and adaptive imitation in uni-manual and bi-manual tasks. Robotics and Autonomous Systems, 54, 370–384.
Bishop, C. M. (2006). Pattern recognition and machine learning. Berlin: Springer.
Caggiano, V., De Santis, A., Siciliano, B., & Chianese, A. (2006). A biomimetic approach to mobility distribution for a human-like redundant arm. In Proc. of the IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics (pp. 393–398).
Chow, C. K., & Liu, C. N. (1968). Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information Theory, 14, 462–467.
Craig, J. J. (1989). Introduction to robotics: mechanisms and control. Reading: Addison Wesley.
Cruse, H., Wischmeyer, E., Bruser, M., Brockfeld, P., & Dress, A. (1990). On the cost functions for the control of the human arm movement. Biological Cybernetics, 62, 519–528.
Flash, T., & Hogan, N. (1985). The coordination of arm movements: an experimentally confirmed mathematical model. Journal of Neuroscience, 5, 1688–1703.
Fod, A., Mataric, M. J., & Jenkins, O. C. (2002). Automated derivation of primitives for movement classification. Autonomous Robots, 12, 39–54.
Ijspeert, A., Nakanishi, J., & Schaal, S. (2004). Movement imitation with nonlinear dynamical systems in humanoid robots. In Proceedings of international conference on robotics and automation (pp. 1398–1403).
Inamura, T., Toshima, I., Tanie, H., & Nakamura, Y. (2004). Embodied symbol emergence based on mimesis theory. International Journal of Robotics Research, 24, 363–378.
Kim, C., Kim, D., & Oh, Y. (2005). Solving an inverse kinematics problem for a humanoid robots imitation of human motions using optimization. In Proc. of int. conf. on informatics in control, automation and robotics (pp. 85–92).
Kovar, L., Gleicher, M., & Pighin, F. (2002). Motion graphs. ACM Transactions on Graphics, 21, 473–482.
Kulic, D., Takano, W., & Nakamura, Y. (2008). Incremental learning, clustering and hierarchy formation of whole body motion patterns using adaptive hidden Markov chains. International Journal of Robotics Research, 27, 761–784.
Lee, J., Chai, J., Reitsma, P. S. A., Hodgins, J. K., & Pollard, N. S. (2002). Interactive control of avatars animated with human motion data. ACM Transactions on Graphics, 21, 491–500.
Ligeois, A. (1977). Automatic supervisory control of the configuration and behavior of multibody mechanism. IEEE Transaction on Systems, Man and Cybernetics, SMC-7(12), 868–871.
Maciejewski, A. A., & Klein, C. A. (1985). Obstacle avoidance for kinematically redundant manipulators in dynamically varying environments. The International Journal of Robotics Research, 4, 109–117.
McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.
Mpompos, N. A., Artemiadis, P. K., Oikonomopoulos, A. S., & Kyriakopoulos, K. J. (2007). Modeling, full identification and control of the Mitsubishi PA-10 robot arm. In Proc. of IEEE/ASME international conference on advanced intelligent mechatronics.
Nakamura, Y., & Hanafusa, H. (1986). Inverse kinematics solution with singularity robustness for robot manipulator control. ASME Journal of Mechanisms, Transmissions, Automation, Design, 108, 163–171.
Pastor, P., Hoffmann, H., Asfour, T., & Schaal, S. (2009). Learning and generalization of motor skills by learning from demonstration. In Proceedings of the 2009 IEEE international conference on robotics and automation.
Pollard, N. S., Hodgins, J. K., Riley, M. J., & Atkeson, C. G. (2002). Adapting human motion for the control of a humanoid robot. In Proc. of IEEE int. conf. on robotics and automation (Vol. 2, pp. 1390–1397).
Potkonjak, V., Popovic, M., Lazarevic, M., & Sinanovic, J. (1998). Redundancy problem in writing: from human to anthropomorphic robot arm. IEEE Transaction on Systems, Man and Cybernetics, part B, 28, 790–805.
Sciavicco, L., & Siciliano, B. (1996). Modeling and control of robot manipulators. New York: McGraw-Hill.
Uno, Y., Kawato, M., & Suzuki, R. (1989). Formation and control of optimal trajectory in human multijoint arm movement. Biological Cybernetics, 61, 89–101.
Xiang, Y. (2002). Probabilistic reasoning in multiagent systems: a graphical models approach. Cambridge: Cambridge University Press.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Artemiadis, P.K., Katsiaris, P.T. & Kyriakopoulos, K.J. A biomimetic approach to inverse kinematics for a redundant robot arm. Auton Robot 29, 293–308 (2010). https://doi.org/10.1007/s10514-010-9196-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10514-010-9196-x