Hand Grasping Choice and Analysis for Tasks

Abstract:

Resulting in an optimal grasping pose of satisfying task requirements is a critical problem for hands manipulation. Based on the problem, taxonomy of grasping poses was created. This paper presents key-based search method that can obtain all hand manipulation poses matching the grasped object. However, these grasping pose must be ranked by combining with task requirements and object geometry. In this way, optimal grasping pose can be achieved. The effectiveness of the method was demonstrated by using grasping pose taxonomy comparisons from motion capture example database.

• Periodical: Applied Mechanics and Materials (Volumes 644-650)
• Pages: 1752-1758
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.644-650.1752
• Online since: September 2014
• Authors: Tao Xu
• Keywords: Constraint, Grasping Evaluation, Hand Manipulation, Motion Capture, Object Geometry, Task Requirement

References

[1] Shihong Xia, Zhaoqi Wang. Recent advances on virtual human synthesis, Science in China Series F: Information Sciences. Vol. 52, No. 5, pp.741-757 (2012).

[2] Onno A. van Nierop. A natural human hand model, The Visual Computer, Vol. 24, No. 1, pp.31-44 (2013).

[3] Albrecht I, Haber J, Seidel HP. Construction and Animation of Anatomically Based Human Hand Models, ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp.98-109 (2013).

[4] W. Tsang, K. Singh, E. Fiume. Helping Hand: An Anatomically Accurate Inverse Dynamics Solution For Unconstrained Hand Motion, ACM SIGGRAPH/Eurographics Symposium of Computer Animation, pp.319-328 (2008).

DOI: 10.1145/1073368.1073414

[5] SUEDA, S., KAUFMAN, A., AND PAI, D. K. Musculotendon simulation for hand animation. ACM Transactions on Graphics, pp.831-838 (2008).

DOI: 10.1145/1360612.1360682

[6] Fleming, J. Rendering tutorial, Computer Arts, 2, cover (2001).

[7] Rohling, R.N., Hollerbach, J.M., Jacobsen, S.C. Optimized fingertip mapping: a general algorithm for robotic hand teleoperation. Presence 2(3), 219-226 (1993).

DOI: 10.1162/pres.1993.2.3.203

[8] Corey Goldfeder, Matei Ciocarlie, Hao Dang and Peter K. Allen. The Columbia Grasp Database. In IEEE Int. Conf. on Robotics and Automation, Kobe, pp.262-271 (2009).

DOI: 10.1109/robot.2009.5152709

[9] Huagen Wan, Shuming Gao. Virtual Grasping for Virtual Assembly Tasks. Proceedings of the Third International Conference on Image and Graphics, pp.448-451 (2004).

DOI: 10.1109/icig.2004.145

[10] Kim, J.; Cordier, F.; Magnenat-Thalmann, N.; Neural network-based violinist's hand animation. Computer Graphics International, Proceedings Digital Object Identifier: pp.37-41 (2000).

DOI: 10.1109/cgi.2000.852318

[11] ELKOURA, G., AND SINGH, K. Handrix: Animating the human hand, ACM SIGGRAPH/EG Symposium on Computer Animation pp.541-552 (2003).

[12] Nancy S. Pollard and Victor B. Zordan. Physically based grasping control from example, ACM SIGGRAPH/Eurographics Symposium on Computer Animation pp.323-333 (8/2005).

DOI: 10.1145/1073368.1073413

[13] Kry Paul, Pai Dinesh. Interaction Capture and Synthesis. ACM Trans. Graph., Vol. 25, No. 3, pp.872-880 (2006).

DOI: 10.1145/1141911.1141969

[14] ]Liu, C. K. Synthesis of interactive hand manipulation, ACM SIGGRAPH/Eurographics symposium on Computer animation, pp.163-17 (2008).

[15] Liu, C.K. Dextrous manipulation from a grasping pose. ACM Trans. Graph. Vol. 28, No. 3 PP. 776-785 (2009).

DOI: 10.1145/1531326.1531365

[16] Jintae Lee, Tosiyasu L. Model-based analysis of hand posture, IEEE Computer Graphics and Applications Vol. 15, No. 5 (9/1995).

DOI: 10.1109/38.403831