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Navigation of Multiple Mobile Robots using Rule-based-Neuro-Fuzzy Technique

Authors: Saroj Kumar Pradhan, Dayal Ramakrushna Parhi, Anup Kumar Panda


This paper deals with motion planning of multiple mobile robots. Mobile robots working together to achieve several objectives have many advantages over single robot system. However, the planning and coordination between the mobile robots is extremely difficult. In the present investigation rule-based and rulebased- neuro-fuzzy techniques are analyzed for multiple mobile robots navigation in an unknown or partially known environment. The final aims of the robots are to reach some pre-defined goals. Based upon a reference motion, direction; distances between the robots and obstacles; and distances between the robots and targets; different types of rules are taken heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and with an attracting influence between the robots and targets. Then a hybrid rule-based-neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation results show that the proposed rulebased- neuro-fuzzy technique can improve navigation performance in complex and unknown environments compared to this simple rulebased technique.

Keywords: Mobile robots, Navigation, Neuro-fuzzy, Obstacle avoidance, Rule-based, Target seeking

Digital Object Identifier (DOI):

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[1] N. T. G├╝rman, "The neural network model RuleNet and its application to mobile robot navigation," Fuzzy Sets and Systems, Volume 85, Issue 2, 23 January 1997, pp. 287-303.
[2] W. Li, C. Ma, F. M. Wahl, "A neuro-fuzzy system architecture for behavior-based control of a mobile robot in unknown environments, " Fuzzy Sets and Systems, Volume 87, Issue 2, 16 April 1997, pp. 133- 140.
[3] C. W. Barfoot, M. Y. Ibrahim, "Development of an adaptive fuzzy behavioural control system with experimental and industrial applications," Computers & Industrial Engineering, Volume 34, Issue 4, September 1998, pp. 807-811.
[4] Jelena and Nigel, "Neuro-fuzzy control of a mobile robot," Neurocomputing, Volume 28, Issues 1-3, October 1999, pp. 127-143.
[5] L. Acosta, G.N. Marichal, L. Moreno, J. A. Méndez, J.J. Rodrigo, "Obstacle Avoidance Using the Human Operator Experience for a Mobile Robot," Journal of Intelligent and Robotic Systems, April 2000, Volume 27, No. 4, pp. 305-319.
[6] G.N. Marichal, L. Acosta, L. Moreno, J.A. Mendez, J.J. Rodrigo, M. Sigut, "Obstacle avoidance for a mobile robot: A neuro-fuzzy approach," Fuzzy Sets and Systems, 1 December 2001, Volume 124, No. 2, pp. 171-179.
[7] K. Althoefer B. Krekelberg, D. Husmeier, L. Seneviratne , "Reinforcement learning in a rule-based navigator for robotic manipulators," Neurocomputing, Volume 37, Issues 1-4 , April 2001, pp. 51-70.
[8] S. Nefti, M. Oussalah, K. Djouani, J. Pontnau, "Intelligent Adaptive Mobile Robot Navigation," Journal of Intelligent and Robotic Systems, April 2001, Volume 30, No. 4, pp. 311-329.
[9] E. Tunstel, A. Howard, H. Seraji, "Rule-based reasoning and neural network perception for safe off-road robot mobility," Expert Systems, September 2002, Volume 19, No. 4, pp. 191-200.
[10] M. A. F. de Souza, M. A. G. V. Ferreira, "Designing reusable rulebased architectures with design patterns," Expert Systems with Applications, Volume 23, Issue 4, November 2002, pp. 395-403.
[11] Y-K. Na and S-Y. Oh, "Hybrid Control for Autonomous Mobile Robot Navigation Using Neural Network Based Behavior Modules and Environment Classification," Autonomous Robots, September 2003, Volume 15, No. 2, pp. 193-206(14).
[12] J. Dietrich, A. Kozlenkov, M. Schroeder, G. Wagner, "Rule-based agents for the semantic web," Electronic Commerce Research and Applications, Volume 2, Issue 4, Winter 2003, pp. 323-338.
[13] B. S. McIntosh, R. I. Muetzelfeldt, C. J. Legg, S. Mazzoleni, P. Csontos, "Reasoning with direction and rate of change in vegetation state transition modeling," Environmental Modelling & Software, Volume 18, Issue 10, December 2003, pp. 915-927.
[14] Clementine Software, Version-5, Available :, 2000.
[15] J.L. Peterson, Petri Net theory and the Modelling of Systems (Prentice- Hall, Englewood Cliff.N.J., 1981).
[16] D.T. Pham, D. R. Parhi, "Navigation of multiple mobile robots using a neural network and a Petri net model," Robotica, U.K., Volume 21, 2003, pp. 79-93
[17] S. K. Pradhan, D. R. Parhi, A. K. Panda, "Neuro-fuzzy techniques for navigation of multiple mobile robots," Fuzzy optimization and decision making, to be published.