A framework of networked visual servo control system with distributed computation

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2010

Without internal affiliation

  • Author: Wu, Haiyan

    Technische Universität München

  • Author: Lou, Lei

    Technische Universität München, Germany

  • Author: Chen, Chih-Chung

    Technische Universität München, Germany

  • Author: Hirche, Sandra

    Technische Universität München, Germany

  • Author: Kühnlenz, Kolja

    Technische Universität München

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In this paper, a networked visual servo control system with distributed computation is proposed to overcome the low sampling rate problem in vision-based control systems. A real-time image data transmission protocol based on Realtime Transport Protocol (RTP) is developed. The captured images are sent to different processing nodes connected over a communication network and processed in parallel. Thus, a high sampling rate of the visual feedback is achieved under a cloud image processing architecture. The varying image processing delay caused by the varying number of extracted features and the random transmission delay are modeled as a random process with Bernoulli distribution. By using the input-delay approach, the resulted networked visual servo control system is reformulated into a stochastic continuous-time system with time-varying delay. Experiments on two 1-DoF linear motor modules are carried out to validate the proposed approach. A visual servo control system without parallel distributed computation is implemented for comparison. The experimental results demonstrate significant performance improvement by the proposed approach.
Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Control, Automation, Robotics and Vision : ICARCV 2010
Publication date2010
Pages1466 - 1471
ISBN (print)978-1-4244-7813-2
StatePublished - 2010


ConferenceInternational Conference on Control Automation Robotics & Vision
CitationsWeb of Science® Times Cited: No match on DOI
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ID: 10205719