• DocumentCode
    530674
  • Title

    A RSSI based localization algorithm for multiple mobile robots

  • Author

    Zhang, Qingxin ; Di, Qinglong ; Xu, Guangyan ; Qiu, Xiaoyan

  • Author_Institution
    Autom. Dept., Shenyang Aerosp. Univ. (SAU), Shenyang, China
  • Volume
    4
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    190
  • Lastpage
    193
  • Abstract
    This paper presents a optimization algorithm to improve the positioning accuracy of the nodes in wireless sensor networks, and introduces RSSI-based (Received Signal Strength Indicator) wireless location technology on formation of multiple mobile robots. First, the RSSI value, which is measured between mobile node and reference node, is optimized by Gaussian model. At the same time, using the classical method to calculate the positioning coordinates of each mobile node with the optimized RSSI values. Then, the position information and the RSSI values between each two mobile nodes are introduced to assist localization. A new optimization algorithm is proposed in this paper. Therefore, the location problem is transformed into a nonlinear optimization problem. The experimental results showed that this method can improve the positioning accuracy of mobile nodes and implements the goal to estimate the positions of all nodes at one time. It provides a basis for the study on positioning of dynamic network and multi-robot formation control.
  • Keywords
    Gaussian processes; mobile robots; optimisation; wireless sensor networks; Gaussian model; RSSI based localization algorithm; multiple mobile robots; nonlinear optimization problem; optimization algorithm; received signal strength indicator; wireless sensor networks; Mobile robots; Robot sensing systems; gaussian model; node localization; nonlinear programming; penalty function method; rssi; wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-7957-3
  • Type

    conf

  • DOI
    10.1109/CMCE.2010.5610184
  • Filename
    5610184