Quantitative measures of cooperation for a dyadic physical interaction task

IEEE-RAS International Conference on Humanoid Robots

Volumn 2015-February, Issue , 2015, Pages 469-474

  Noohi, Ehsan ^a   Žefran, Miloš ^a  

^a University of Illinois at Chicago   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATION TASK; COLLABORATIVE TASKS; COMPREHENSIVE MODEL; EMPIRICAL STUDIES; HUMAN SUBJECTS; PHYSICAL INTERACTIONS; QUANTITATIVE MEASURES;

ANTHROPOMORPHIC ROBOTS;

EID: 84945192730     PISSN: 21640572     EISSN: 21640580     Source Type: Conference Proceeding    
DOI: 10.1109/HUMANOIDS.2014.7041403     Document Type: Conference Paper

References (18)

1. K. Abdel-Malek and J. Yang, Human Performance Measures: Mathematics, Dept of Mech Engr, University of Iowa, Tech. Rep., 2005
2. T. Yoshikawa, Manipulability and redundancy control of robotic mechanisms, in IEEE ICRA, vol. 2, Mar 1985, pp. 1004-1009
3. J. P. Merlet, Jacobian, Manipulability, Condition Number, and Accuracy of Parallel Robots, Journal of Mechanical Design, vol. 128, no. 1, p. 199, 2006
4. A. Bicchi and D. Prattichizzo, Manipulability of cooperating robots with unactuated joints and closed-chain mechanisms, IEEE Transactions on Robotics and Automation, vol. 16, no. 4, pp. 336-345, 2000
5. T. Flash and N. Hogan, The coordination of arm movements: An experimentally confirmed mathematical model, Journal of neuroscience, vol. 5, no. 7, pp. 1688-1703, 1985
6. P. M. Fitts, The information capacity of the human motor system in controlling the amplitude of movement. Journal of experimental psychology, vol. 47, pp. 381-391, 1954
7. G. Garvin, M. Žefran, E. Henis, and V. Kumar, Two-arm trajectory planning in a manipulation task, Biological Cybernetics, vol. 76, no. 1, pp. 53-62, 1997
8. American National Standard, Guide to Human Performance Measurements. American Institute of Aeronautics and Astronautics, 2000
9. G. Ganesh, A. Takagi, R. Osu, T. Yoshioka, M. Kawato, and E. Burdet, Two is better than one: physical interactions improve motor performance in humans. Scientific reports, vol. 4, p. 3824, Jan. 2014
10. R. P. van der Wel, G. Knoblich, and N. Sebanz, Let the force be with us: dyads exploit haptic coupling for coordination. Journal of experimental psychology, human perception and performance, vol. 37, no. 5, pp. 1420-31, Oct. 2011
11. R. Groten, D. Feth, A. Peer, M. Buss, and R. Klatzky, Efficiency analysis in a collaborative task with reciprocal haptic feedback, IEEE/RSJ IROS, pp. 461-466, Oct. 2009
12. S. Singer and D. Akin, A Survey of Quantitative Team Performance Metrics for Human-Robot Collaboration, International Conference on Environmental Systems, no. July, pp. 1-19, 2011
13. R. Madhavan, E. Tunstel, and E. Messina, Performance Evaluation and Benchmarking of Intelligent Systems. Springer US, 2009
14. A. Steinfeld, T. Fong, D. Kaber, M. Lewis, J. Scholtz, A. Schultz, and M. Goodrich, Common metrics for human-robot interaction, The 1st ACM Conference on Human-robot Interaction, pp. 33-40, 2006
15. A. Mortl, M. Lawitzky, A. Kucukyilmaz, M. Sezgin, C. Basdogan, and S. Hirche, The role of roles: Physical cooperation between humans and robots, The International Journal of Robotics Research, vol. 31, no. 13, pp. 1656-1674, Aug. 2012
16. D. Feth, R. Groten, A. Peer, S. Hirche, and M. Buss, Performance related energy exchange in haptic human-human interaction in a shared virtual object manipulation task, World Haptics, pp. 338-343, 2009
17. M. Kawato, Internal models for motor control and trajectory planning, Curr. Opin. in Neurobiology, vol. 9, no. 6, pp. 718-727, 1999
18. K. Reed, M. Peshkin, M. J. Hartmann, M. Grabowecky, J. Patton, and P. M. Vishton, Haptically linked dyads: are two motor-control systems better than one? Psychological science, vol. 17, no. 5, pp. 365-6, May 2006