Forecasting the development of the biped robot walking technique in Japan through S-curve model analysis

Chen-Yuan Liu () and Jhen-Cheng Wang
Additional contact information
Chen-Yuan Liu: Tungnan University
Jhen-Cheng Wang: Tungnan University

Scientometrics, 2010, vol. 82, issue 1, No 4, 36 pages

Abstract: Abstract Patents contain much significant technical information which can serve as an indicator of technological and economical development. This study attempts to forecast the development of the biped robot walking technique in Japan by use of the patent data obtained from the Japan Patent Office. The study applies linear regression to the patent data using three S-curve models developed by Loglet Lab, Pearl, and Gompertz individually. Various parameters inherent to each model including the least sum of modulus error and the least mean of square error of the model are analyzed. The most appropriate model for measuring the inflection point, the growth and the saturation time of the technique is described. Based on the Gompertz model analysis, this study finds that the biped robot walking technique will continue to develop for several decades in Japan and the saturation period is estimated to be around the year 2079–2082. This finding can help related researchers and managers in the robot field to foresee the development trend of the biped robot walking technique in this century.

Keywords: Patent growth trend; Forecast; S curve; The walking technique of the biped robot (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-009-0055-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:82:y:2010:i:1:d:10.1007_s11192-009-0055-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-009-0055-5

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().