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Coordinating the motion of mobile robots using Cellular Neural Network

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This paper presents a method for motion planning for a group of mobile robots. The goal of the group is to move through an environment and to reach a destination while maintaining the desired formation. The map of the environment is represented as a grid of cells. A state of each cell is determined. It can be free, occupied by the obstacle, occupied by a robot. The trajectories of the robots are planned using the modification of diffusion method. The algorithm is implemented using Cellular Neural Network. This kind of implementation allows of efficient path planning and to solve conflicts between robots. Computer simulations were preformed in order to proof the efficiency of the approach.
Twórcy
  • PhD works for Warsaw University of Technology, Faculty of Mechatronics, Św. Andrzeja Boboli 8 street, 02-525 Warsaw, Poland and Institute of Fundamental Technological Research, Polish Academy of Sciences, 00-049 Świętokrzyska str., warsaw, Poland, bsiem@ippt.gov.pl
Bibliografia
  • [1]  T. Arai and J. Ota, "Motion Planning of multiple mobile robots", Proc. of the 1992 IEEE International Conference on Intelligent Robots and Systems, pp. 261-268.
  • [2]  R.C.   Arkin,   Behavior-based   robotics,   MIT   Press, Cambridge, 1998.
  • [3]  K. Azarm and G. Schmidt, "A decentralized approach for the conflict-free motion of multiple mobile robots", Proc. of IROS, 1996, pp. 1667-1673.
  • [4]  T. Balch and R.C. Arkin, "Behavior-based formation control for multirobot teams", IEEE Trans, on Robotics and Automation, 1998, pp. 926-939.
  • [5]  B. Barraquand, J.C. Langois, J. C. Latombe, "Numerical potential field techniques for robot path planning", IEEE Trans, on Robotics and Automation, vol 22, issue 2, 1992, pp. 224-241.
  • [6]  M.  Bennewitz, W.  Burgard, S. Thrun,  "Optimizing schedules for prioritized path planning of multi-robot systems", Proc. of the IEEE International Conference on Robotics Automation (ICRA), 2000.
  • [7]  Z.   Bien  and X.   Lee,  "A  minimum-time trajectory planning method for two robots", IEEE Transactions on Robotics and Automation, vol. 8, issue 3, 1992, pp. 414-418.
  • [8] L. Chua and L. Young, "Cellular Neural Network", IEEE Transaction on Circuit System, 1990, pp. 500-505.
  • [9] L. Chua , "CNN A Vision of Complexity", Int. Journal of Bifurcation and Chaos, vol.7,1997, pp. 2219-2425.
  • [10] K. S. Evans, C. Unsal, J. S. Bay, "A reactive coordination scheme for many-robot system", IEEE Trans, on Systems, 1997,pp.598-610.
  • [11] Y. Guo and L E. Parker, "A distributed and Optimal Motion Planning Approach for Multiple Mobile Robots", Proc. of ICRA, 2002, pp. 2612-2619.
  • [12] K. A. Konolige, "Gradient Method for Realtime Robot Control", IROS, 2000, pp. 639646.
  • [13] P. Orgen, N. E. Leonard, "A Convergent Dynamic Window Approach to Obstacle Avoidance", IEEE Transaction on Robotics, 2005.
  • [14] B. Siemiątkowska, "Cellular Neural Network for Path Planning", Proc. of SIRS, 2000, pp. 125-130.
  • [15] C. Warren, "Multiple robot path coordination using artificial potential fields", Proc. of ICRA, pp. 500-505, 1990 Addison-Wesley, 1986.
  • [16] B. Siemiątkowska, R. Chojecki, M. Olszewski, „Zastosowanie wielowarstwowych sieci komórkowych do planowania trasy dla robota mobilnego" [Application of multi-layer celi networks for route's planning of a mobile robot], Krajowa Konferencja Robotyki, Poland, 2006.
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Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUJ5-0020-0009
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