Browse > Article
http://dx.doi.org/10.7746/jkros.2012.7.3.194

Task Complexity of Movement Skills for Robots  

Kwon, Woo-Young (Department of Electronics and Computer Engineering, Hanyang University)
Suh, Il-Hong (Department of Electronics and Computer Engineering, Hanyang University)
Lee, Jun-Goo (Department of Electronics and Computer Engineering, Hanyang University)
You, Bum-Jae (Korea Institute of Science and Technology)
Oh, Sang-Rok (Korea Institute of Science and Technology)
Publication Information
The Journal of Korea Robotics Society / v.7, no.3, 2012 , pp. 194-204 More about this Journal
Abstract
Measuring task complexity of movement skill is an important factor to evaluate a difficulty of learning and/or imitating a task for autonomous robots. Although many complexity-measures are proposed in research areas such as neuroscience, physics, computer science, and biology, there have been little attention on the robotic tasks. To cope with measuring complexity of robotic task, we propose an information-theoretic measure for task complexity of movement skills. By modeling proprioceptive as well as exteroceptive sensor data as multivariate Gaussian distribution, movements of a task can be modeled as probabilistic model. Additionally, complexity of temporal variations is modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on the real robotic movement tasks.
Keywords
Complexity; Task Complexity; Movement Skills; Neural Complexity;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M. Li and P. Vit'anyi, An introduction to Kolmogorov complexity and its applications. Springer-Verlag New York Inc, 2008.
2 R. Lopez-Ruiz, H. Mancini, and X. Calbet, "A statistical measure of complexity," Physics Letters A, vol. 209, no. 5-6, pp. 321-326, 1995.   DOI
3 G. Tononi, O. Sporns, and G. Edelman, "A measure for brain complexity: relating functional segregation and integration in the nervous system," Proceedings of the National Academy of Sciences, vol. 91, no. 11, p. 5033, 1994.   DOI
4 G. Tononi, G. Edelman, and O. Sporns, "Complexity and coherency: integrating information in the brain," Trends in cognitive sciences, vol. 2, no. 12, pp. 474-484, 1998.   DOI   ScienceOn
5 G. Tononi, "Information integration: its relevance to brain function and consciousness," Archives italiennes de biologie, vol. 148, no. 3, pp. 299--322, 2010.
6 L. Barnett, C. Buckley, and S. Bullock, "Neural complexity and structural connectivity," Physical Review E, vol. 79, no. 5, p. 051914, 2009.   DOI
7 L. Barnett, C. Buckley, and S. Bullock, "Neural complexity: A graph theoretic interpretation," Physical Review E, vol. 83, no. 4, p. 041906, 2011.   DOI
8 L. Smith, "A tutorial on principal components analysis," Cornell University, USA, vol. 51, 2002.
9 C. Bishop and S. S. en ligne), Pattern recognition and machine learning. springer New York, 2006, vol. 4.
10 OptiTrack, "Optitrack technical specifications: v100-r2," http://www.naturalpoint.com/optitrack /products/v100-r2/specs.html.
11 Kwang-Tae Jung, Won-dea Jung, and Jin-Kyun Park, "Fuzzy Linguistic Approach for Evaluating Task Complexity in Nuclear Power Plant", Journal of the KOSOS, Vol. 20, No. 1,pp. 126-132, 2005
12 J. Flack and D. Krakauer, "Challenges for complexity measures: A perspective from social dynamics and collective social computation," Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 21, no. 3, pp. 037 108--037 108, 2011.   DOI
13 P. Robinson, "Task complexity, task difficulty, and task production: Exploring interactions in a componential framework," Applied Linguistics, vol. 22, no. 1, pp. 27-57, 2001.   DOI
14 K. Bystrom and K. J¨arvelin, "Task complexity affects information seeking and use," Information Processing & Management, vol. 31, no. 2, pp. 191-213, 1995.   DOI
15 J. Teo and H. Abbass, "Multiobjectivity and complexity in embodied cognition," Evolutionary Computation, IEEE Transactions on, vol. 9, no. 4, pp. 337-360, 2005.   DOI
16 A. Seth and G. Edelman, "Environment and behavior influence the complexity of evolved neural networks," Adaptive Behavior, vol. 12, no. 1, pp. 5-20, 2004.   DOI
17 A. Sanderson, "Parts entropy methods for robotic assembly system design," in Robotics and Automation. Proceedings. 1984 IEEE InternationalConference on, vol. 1. IEEE, 1984, pp. 600- -608.
18 H. Simon, "The architecture of complexity," Proceedings of the American philosophical society, vol. 106, no. 6, pp. 467-482, 1962.
19 G. Chirikjian, "Parts entropy and the principal kinematic formula," Stochastic Models, Information Theory, and Lie Groups, Volume 2, pp. 187-228, 2012.
20 M. Moll and M. Erdmann, "Manipulation of pose distributions," The International Journal of Robotics Research, vol. 21, no. 3, pp. 277-292, 2002.   DOI