• DocumentCode
    2011102
  • Title

    Towards real-time multi-sensor information retrieval in Cloud Robotic System

  • Author

    Wang, Lujia ; Liu, Ming ; Meng, Max Q -H ; Siegwart, Roland

  • Author_Institution
    Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2012
  • fDate
    13-15 Sept. 2012
  • Firstpage
    21
  • Lastpage
    26
  • Abstract
    Cloud Robotics is currently driving interest in both academia and industry. It allows different types of robots to share information and develop new skills even without specific sensors. They can also perform intensive tasks by combining multiple robots with a cooperative manner. Multi-sensor data retrieval is one of the fundamental tasks for resource sharing demanded by Cloud Robotic system. However, many technical challenges persist, for example Multi-Sensor Data Retrieval (MSDR) is particularly difficult when Cloud Cluster Hosts accommodate unpredictable data requested by multi robots in parallel. Moreover, the synchronization of multi-sensor data mostly requires near real-time response of different message types. In this paper, we describe a MSDR framework which is comprised of priority scheduling method and buffer management scheme. It is validated by assessing the quality of service (QoS) model in the sense of facilitating data retrieval management. Experiments show that the proposed framework achieves better performance in typical Cloud Robotics scenarios.
  • Keywords
    buffer storage; cloud computing; control engineering computing; multi-robot systems; quality of service; scheduling; sensor fusion; QoS model; buffer management scheme; cloud cluster host; cloud robotic system; multiple robot; multisensor data retrieval; multisensor information retrieval; priority scheduling method; quality of service model; resource sharing; Bandwidth; Databases; Protocols; Quality of service; Resource management; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on
  • Conference_Location
    Hamburg
  • Print_ISBN
    978-1-4673-2510-3
  • Electronic_ISBN
    978-1-4673-2511-0
  • Type

    conf

  • DOI
    10.1109/MFI.2012.6343054
  • Filename
    6343054