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   Modeling a sensor to improve its efficacy  
   
نویسنده malakar n.k. ,gladkov d. ,knuth k.h.
منبع journal of sensors - 2013 - دوره : 2013 - شماره : 0
چکیده    Robots rely on sensors to provide them with information about their surroundings. however,high-quality sensors can be extremely expensive and cost-prohibitive. thus many robotic systems must make due with lower-quality sensors. here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a bayesian inferential framework. as a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive lego light sensor to estimate the position and radius of a white circle on a black field. the light sensor integrates the light arriving from a spatially distributed region within its field of view weighted by its spatial sensitivity function (ssf). we demonstrate that by incorporating an accurate model of the light sensor ssf into the likelihood function of a bayesian inference engine,an autonomous system can make improved inferences about its surroundings. the method presented here is data based,fairly general,and made with plug-and-play in mind so that it could be implemented in similar problems. © 2013 nabin k. malakar et al.
آدرس w. b. hanson center for space sciences,university of texas at dallas,richardson, United States, department of physics,university at albany (suny),albany, United States, departments of physics and informatics,university at albany (suny),albany, United States
 
     
   
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