DocumentCode
2116195
Title
Statistical modeling and design issues of a crossbeam sensor
Author
Wang, Xiao-Gang ; Shen, H.C. ; Moallem, M.
Volume
3
fYear
2001
fDate
2001
Firstpage
1452
Abstract
The basic idea of RISC (reduced intricacy sensing and control) robotics is an attempt to perform challenging industrial manufacturing tasks by using a combination of simple hardware and sophisticated algorithms. Many effective strategies and algorithms have been explored. However, the issue of optimal design of RISC sensor has not been solved. The main reason is the shortage of good models. In this paper, we propose a statistical model for one of the typical RISC sensors, i.e. the crossbeam sensor. Based on this statistical model we employ the multiple hypotheses-testing method as optimal design technique and present its applied strategies. It is believed that this work will lead to development of new RISC sensors because a new principle and a pertinent model are introduced into this area
Keywords
industrial robots; optical sensors; optimisation; statistical analysis; RISC robotics; crossbeam sensor design issues; industrial manufacturing tasks; multiple hypotheses-testing method; optimal design technique; reduced intricacy control; reduced intricacy sensing; statistical modeling; Density functional theory; Hardware; Manufacturing industries; Object recognition; Optical arrays; Reduced instruction set computing; Robot control; Robot sensing systems; Sensor arrays; Service robots;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on
Conference_Location
Maui, HI
Print_ISBN
0-7803-6612-3
Type
conf
DOI
10.1109/IROS.2001.977185
Filename
977185
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