DocumentCode
3538094
Title
Autonomous sensor placement
Author
Knuth, Kevin H. ; Center, Julian L.
Author_Institution
Depts. of Phys. & Inf., Univ. at Albany, Albany, NY
fYear
2008
fDate
10-11 Nov. 2008
Firstpage
94
Lastpage
99
Abstract
With an increasing reliance on robotic platforms to perform scientific exploration in remote or hostile environments, it is becoming crucial that robotic systems be able to perform autonomous intelligent sensor placement as well as autonomous experimental design. Such a system requires encoding of scientific knowledge, the ability to make inferences from data, and the ability to identify the most relevant question to ask given both the instrumentpsilas prior knowledge and the issue it is designed to address. This requires implementation of two computational engines: the inference engine and the inquiry engine. Here we demonstrate our first efforts to develop intelligent instruments that rely on autonomous sensor placement.
Keywords
Bayes methods; Markov processes; Monte Carlo methods; design of experiments; intelligent robots; manipulators; sensors; Bayesian Markov chain Monte Carlo algorithm; autonomous experimental design; autonomous intelligent sensor placement; inference engine; inquiry engine; robotic arm; scientific exploration; scientific knowledge encoding; Bayesian methods; Design for experiments; Engines; Instruments; Intelligent robots; Intelligent sensors; Position measurement; Robot kinematics; Robot sensing systems; Robotics and automation;
fLanguage
English
Publisher
ieee
Conference_Titel
Technologies for Practical Robot Applications, 2008. TePRA 2008. IEEE International Conference on
Conference_Location
Woburn, MA
Print_ISBN
978-1-4244-2791-8
Electronic_ISBN
978-1-4244-2792-5
Type
conf
DOI
10.1109/TEPRA.2008.4686680
Filename
4686680
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