Abstract
As a compactness unit, the human hand shows high versatility and sophisticated grasp functionality. How to design a robot hand replicating the human grasp posture is a challenging task. Mechanical implementation of postural synergies provides new hope for resolving this problem. Generally, these posture synergies are extracted from a large data set consisting of a variety of hand grasp postures that can be reconstructed through synergies with an acceptable error. In the daily life, people can successfully grasp an object within a grasp tolerance (acceptable scope of relative position between human hand and objects). However, the relative position between human hand and objects is almost ignored in previous studies on the reconstruction of human grasp postures. In this paper, we tend to analyze the difference of the reconstruction of hand postures in two different scenarios: constraint and non-constraint wrist positions. The principal component analysis (PCA) is applied to the posture data sets acquired under two different data-acquisition paradigms, with steady and varying wrist-object position, respectively, for reconstructing the hand postures. The reconstruction differences between these two data-collection paradigms are analyzed. The information transmission rates given by different number of PCs are qualified. The distributions of the first four PCs elements under the two paradigms are also presented, respectively. Our results show that the specific hand postures in changing relative position within grasp tolerance can be faithfully reconstructed only when the relative position between the human hand and the object are fully considered.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Schlesinger, G.: Der mechanische Aufbau der kunstlichen Glieder, Ersatzglieder und Arbeitshilfen für Kriegsbeschädigte und Unfallverletzte (1919)
Napier, J.R.: The prehensile movements of the human hand. Journal of Bone and Joint Surgery 38(4), 902–913 (1956)
Cutkosky, M.R.: On grasp choice, grasp models, and the design of hands for manufacturing tasks. IEEE Transactions on Robotics and Automation 5(3), 269–279 (1989)
Feix, T., Pawlik, R., Schmiedmayer, H.-B., Romero, J., Kragić, D.: A comprehensive grasp taxonomy. In: Robotics, Science and Systems Conference (RSS). Seattle, Washington, USA (2009)
Zheng, J.Z., De La Rosa, S., Dollar, A.M.: An investigation of grasp type and frequency in daily household and machine shop tasks. In: IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, pp. 4169–4175 (2011)
Bullock, I.M., Feix, T., Dollar, A.M.: Finding small, versatile sets of human grasps to span common objects. In: IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, pp. 1060–1067 (2013)
Santello, M., Flanders, M., Soechting, J.: Postural hand synergies for tool use. The Journal of Neuroscience 18(23), 10 105–10 115 (1998)
Brown, C.Y., Asada, H.H.: Inter-finger coordination and postural synergies in robot hands via mechanical implementation of principal components analysis. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, USA, pp. 2877–2882 (2007)
Xu, K., Liu, H., Du, Y., Sheng, X., Zhu, X.: Mechanical implementation of postural synergies using a simple continuum mechanism. In: IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, pp. 1348–1353 (2014)
Xu, K., Liu, H., Du, Y., Zhu, X.: Design of an underactuated anthropomorphic hand with mechanically implemented postural synergies. Advanced Robotics 28(21), 1459–1474 (2014)
Li, S., Sheng, X., Liu, H., Zhu, X.: Design of a myoelectric prosthetic hand implementing postural synergy mechanically. Industrial Robot: An International Journal 41(5), 447–455 (2014)
Rosmarin, J.B., Asada, H.H.: Synergistic design of a humanoid hand with hybrid dc motor-sma array actuators embedded in the palm. In: IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA, 773–778 (2008)
Sun, B., Xiong, C., Chen, W., Zhang, Q., Liu, M., Zhang, Q.: A novel design method of anthropomorphic prosthetic hands for reproducing human hand grasping. In: IEEE International Conference of Engineering in Medicine and Biology Society (EMBC), Chicago, USA, pp. 6215–6221 (2014)
Chen, W., Xiong, C., Liu, M., Liu, M.: Characteristics analysis and mechanical implementation of human finger movements. In: IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, pp. 403–408 (2014)
Catalano, M.G., Grioli, G., Farnioli, E., et al.: Adaptive synergies for the design and control of the Pisa/IIT SoftHand. The International Journal of Robotics Research 33(5), 768–782 (2014)
Eckart, C., Young, G.: The approximation of one matrix by another of lower rank. Psychometrika 1, 211–218 (1936)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Jiang, L., Liu, Y., Yang, D., Liu, H. (2015). Analysis of Human Hand Posture Reconstruction Under Constraint and Non-constraint Wrist Position. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9244. Springer, Cham. https://doi.org/10.1007/978-3-319-22879-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-22879-2_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22878-5
Online ISBN: 978-3-319-22879-2
eBook Packages: Computer ScienceComputer Science (R0)