• DocumentCode
    1194930
  • Title

    A Neural Network Approach to Dynamic Task Assignment of Multirobots

  • Author

    Anmin Zhu ; Yang, S.X.

  • Volume
    17
  • Issue
    5
  • fYear
    2006
  • Firstpage
    1278
  • Lastpage
    1287
  • Abstract
    In this paper, a neural network approach to task assignment, based on a self-organizing map (SOM), is proposed for a multirobot system in dynamic environments subject to uncertainties. It is capable of dynamically controlling a group of mobile robots to achieve multiple tasks at different locations, so that the desired number of robots will arrive at every target location from arbitrary initial locations. In the proposed approach, the robot motion planning is integrated with the task assignment, thus the robots start to move once the overall task is given. The robot navigation can be dynamically adjusted to guarantee that each target location has the desired number of robots, even under uncertainties such as when some robots break down. The proposed approach is capable of dealing with changing environments. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies
  • Keywords
    control engineering computing; mobile robots; multi-robot systems; path planning; self-organising feature maps; dynamic task assignment; mobile robots; multirobot system; neural network approach; robot motion planning; self-organizing map; target location; Heuristic algorithms; Intelligent robots; Intelligent systems; Mobile robots; Motion planning; Multirobot systems; Neural networks; Pattern formation; Robot kinematics; Uncertainty; Multirobots; neural network; self-organizing map (SOM); task assignment; Algorithms; Artificial Intelligence; Computing Methodologies; Decision Support Techniques; Kinetics; Neural Networks (Computer); Pattern Recognition, Automated; Robotics;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2006.875994
  • Filename
    1687936