Weibull Distribution: User Performance Analyses for Telerobotics System Interface
(*) Corresponding author
DOI: https://doi.org/10.15866/ireaco.v10i2.10581
Abstract
When aiming to improve interfaces for remote devices, methods are required for assessing them and comparing the effect of changes. Distributions provide a means of summarizing data and a model that produces a particular distribution is known, so that if the data is found to match a known distribution a useful model is available for interpreting the data. This paper presents the analysis using the Weibull distribution to evaluate the user performance of the prototype telerobotics user interface. This prototype was deployed for public testing at an exhibition in the CSIRO Discovery Centre, Canberra, Australia, over three months. An investigation of operator requests to three models of telerobotics control from a total of 6139 total user sessions was found to fit Weibull distributions. All of the devices offered operators the opportunity to manipulate wooden blocks through the application with three model controls. Usage patterns were quite different on the different control models, but operator behavior could be characterized by the two parameters of the Weibull distribution. One of the parameters, the shape parameter, was found to be nearly invariant so the comparison could be reduced to the scale parameter. This meant interfaces can be compared with a single value calculated from automatically captured data during use of the interface.
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D. N. P. Murthy, et al., Weibull Model. Hoboken, New Jesery: Wiley Interscience, 2004.
http://dx.doi.org/10.1002/047147326x
Benaicha, H., Chaker, A., Weibull Mixture Model for Reliability Analysis, (2014) International Review of Electrical Engineering (IREE), 9 (5), pp. 986-990.
http://dx.doi.org/10.15866/iree.v9i5.4021
Maouedj, R., Benyoucef, B., A Statistical Analysis of Wind Power Density Based on the Weibull and Rayleigh Models at Six Regions of Algeria, (2015) International Journal on Energy Conversion (IRECON), 3 (2), pp. 60-67.
B. S. Blanchard, Logistics Engineering and Management, Fourth ed. Englewood Cliffs, New Jersey.: Prentice-Hall, Inc., 1992.
http://dx.doi.org/10.7202/029029ar
N. L. Johnson, et al., Continues Univariate Distribution, second edition ed. vol. 1. New York: Wiley, 1994.
http://dx.doi.org/10.1002/0471715816.ch3
K. Taylor, "Web Telerobotics: Reducing Complexity In Robotics," Doctor of Philosophy, Department of Mechanical and Materials Engineering, University of Western Australia, Perth, Western Australia, 1999
http://dx.doi.org/10.17140/hroj-2-118
K. Krishnamoorthy, Handbook of Statistical Distribution with Applications. USA: Chapman & Hall/CRC, 2006.
http://dx.doi.org/10.1201/9781420017380
I. Engineered Software. (18/12/2012). Weibull Distribution. Available: http://www.engineeredsoftware.com/nasa/weibull.htm
R. E. Walpole and R. H. Myers, Probability and Statistics for Engineers and Scientists (Fourth Edition). New York: Macmilan, 1989.
http://dx.doi.org/10.2307/2530629
V. Ricci, "Fitting distributions with R" cran.r-project, Feb. 21, 2005.
http://dx.doi.org/10.1081/stm-200056227
Masmoudi, M., Kaddour El Boudadi, L., Loukil, A., Vareille, J., Real-Time Prediction of RTT Based on Holt-Winters Method for Internet-Based Teleoperation, (2015) International Review on Computers and Software (IRECOS), 10 (1), pp. 72-79.
http://dx.doi.org/10.15866/irecos.v10i1.5164
T. Indow, "Weibull Form in Memory, Reaction Time, and Social Behaviour: Asymptotic Distribution of Minima from Heterogenous Population," Univ. of California, Irvine, MBS 95-04, 1995.
http://dx.doi.org/10.2514/3.12808
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