A neuro-fuzzy controller for mobile robot navigation and multirobot convoying

A Neural integrated Fuzzy conTroller (NiF-T) which integrates the fuzzy logic representation of human knowledge with the learning capability of neural networks is developed for nonlinear dynamic control problems. NiF-T architecture comprises of three distinct parts: (1) Fuzzy logic Membership Functions (FMF), (2) a Rule Neural Network (RNN), and (3) an Output-Refinement Neural Network (ORNN). FMF are utilized to fuzzify sensory inputs. RNN interpolates the fuzzy rule set; after defuzzification, the output is used to train ORNN. The weights of the ORNN can be adjusted on-line to fine-tune the controller. In this paper, real-time implementations of autonomous mobile robot navigation and multirobot convoying behavior utilizing the NiF-T are presented. Only five rules were used to train the wall following behavior, while nine were used for the hall centering. Also, a robot convoying behavior was realized with only nine rules. For all of the described behaviors-wall following, hall centering, and convoying, their RNN's are trained only for a few hundred iterations and so are their ORNN's trained for only less than one hundred iterations to learn their parent rule sets.

[1]  Naohiro Fukumura,et al.  Learning goal-directed navigation as attractor dynamics for a sensory motor system. (An experiment by the mobile robot YAMABICO) , 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

[2]  Akira Ichikawa,et al.  Application of neural networks to fuzzy control , 1993, Neural Networks.

[3]  Witold Pedrycz,et al.  Fuzzy-set based models of neurons and knowledge-based networks , 1993, IEEE Trans. Fuzzy Syst..

[4]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[5]  Fumihito Arai,et al.  Navigation system based on ceiling landmark recognition for autonomous mobile robot-landmark detection based on fuzzy template matching (FTM) , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[6]  Ewald von Puttkamer,et al.  Realtime-learning on an autonomous mobile robot with neural networks , 1994, Proceedings Sixth Euromicro Workshop on Real-Time Systems.

[7]  Hisao Ishibuchi,et al.  Neural networks that learn from fuzzy if-then rules , 1993, IEEE Trans. Fuzzy Syst..

[8]  D. Pomerleau,et al.  MANIAC : A Next Generation Neurally Based Autonomous Road Follower , 1993 .

[9]  K. Asakawa,et al.  Mobile robot control by a structured hierarchical neural network , 1990, IEEE Control Systems Magazine.

[10]  John J. Leonard,et al.  Directed Sonar Sensing for Mobile Robot Navigation , 1992 .

[11]  Leonardo Maria Reyneri,et al.  Cintia: a neuro-fuzzy real-time controller for low-power embedded systems , 1995, IEEE Micro.

[12]  Pai-Shih lee,et al.  Collision avoidance by fuzzy logic control for automated guided vehicle navigation , 1994, J. Field Robotics.

[13]  Paul Keng-Chieh Wang.  Navigation strategies for multiple autonomous mobile robots moving in formation , 1991, J. Field Robotics.

[14]  R. M. H. Cheng,et al.  Neuromorphic controller for AGV steering , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[15]  Stan C. A. M. Gielen,et al.  Neural Network Dynamics for Path Planning and Obstacle Avoidance , 1995, Neural Networks.

[16]  Rodney M. Goodman,et al.  Fuzzy rule-based networks for control , 1994, IEEE Trans. Fuzzy Syst..

[17]  K. C. Ng.  Fuzzy logic controller and real-time implementation of a ball balancing beam , 1995 .

[18]  Martin Nilsson,et al.  Cooperative multi-robot box-pushing , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[19]  Joseph M. Lubin,et al.  Analysis of a neural network lateral controller for an autonomous road vehicle , 1992 .

[20]  Yasuo Morooka,et al.  Fuzzy and Neural Hybrid Expert Systems: Synergetic AI , 1995, IEEE Expert.

[21]  Fabrice R. Noreils,et al.  Toward a Robot Architecture Integrating Cooperation between Mobile Robots: Application to Indoor Environment , 1993, Int. J. Robotics Res..

[22]  Mohan M. Trivedi.  Intelligent robotic systems: control and cooperation , 1995, Defense, Security, and Sensing.

[23]  Alex Fukunaga,et al.  Cooperative mobile robotics: antecedents and directions , 1995 .

[24]  Yoshiki Uchikawa,et al.  On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm , 1992, IEEE Trans. Neural Networks.

[25]  H. Surmann,et al.  A fuzzy system for indoor mobile robot navigation , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[26]  Mohan M. Trivedi,et al.  Motion control of cooperative robotic teams through visual observation and fuzzy logic control , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[27]  Lynne E. Parker.  The effect of action recognition and robot awareness in cooperative robotic teams , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[28]  Avinash C. Kak,et al.  NEURO-NAV: a neural network based architecture for vision-guided mobile robot navigation using non-metrical models of the environment , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[29]  Hajime Asama,et al.  Functional distribution among multiple mobile robots in an autonomous and decentralized robot system , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[30]  Michael R. M. Jenkin,et al.  Experiments in sensing and communication for robot convoy navigation , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[31]  Bruce Randall Donald,et al.  Moving furniture with teams of autonomous robots , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[32]  Mohan M. Trivedi,et al.  Neural integrated fuzzy controller (NiF-T) and real-time implementation of a ball balancing beam (BBB) , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[33]  Mohan M. Trivedi,et al.  MoNiF: a modular neuro-fuzzy controller for race car navigation , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[34]  Mohan M. Trivedi,et al.  Reactive locomotion control of articulated-tracked mobile robots for obstacle negotiation , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[35]  S. Ito,et al.  Navigation system based on ceiling landmark recognition for autonomous mobile robot , 1993, Proceedings of IECON '93 - 19th Annual Conference of IEEE Industrial Electronics.

[36]  Hamid R. Berenji,et al.  Learning and tuning fuzzy logic controllers through reinforcements , 1992, IEEE Trans. Neural Networks.

[37]  Eiichi Yoshida,et al.  An algorithm of dividing a work area to multiple mobile robots , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[38]  State-Space Search.  Optimal Assignment of Robot Tasks with Precedence for Multi-Robot Coordination , 1995 .

[39]  Ricardo Gutierrez-Osuna,et al.  Global self-localization for autonomous mobile robots using self-organizing Kohonen neural networks , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.