• 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