Gross motion planning—a survey
ACM Computing Surveys (CSUR)
Predictive fuzzy control of an autonomous mobile robot with forecast learning function
Fuzzy Sets and Systems
Fuzzy system modeling by fuzzy partition and GA hybrid schemes
Fuzzy Sets and Systems
A fuzzy classifier system for evolutionary learning of robot behaviors
Applied Mathematics and Computation - Special issue on articficial life and robotics
Robot Motion Planning
Petri Net Theory and the Modeling of Systems
Petri Net Theory and the Modeling of Systems
Fuzzy Motion Planning of Mobile Robots in Unknown Environments
Journal of Intelligent and Robotic Systems
Potential field method to navigate several mobile robots
Applied Intelligence
Design of a fuzzy controller in mobile robotics using genetic algorithms
Applied Soft Computing
Mobile robot navigation using motor schema and fuzzy context dependent behavior modulation
Applied Soft Computing
The stable and precise motion control for multiple mobile robots
Applied Soft Computing
Intelligent neuro-controller for navigation of mobile robot
Proceedings of the International Conference on Advances in Computing, Communication and Control
Expert Systems with Applications: An International Journal
Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning
Artificial Intelligence Review
Evolving robotic path with genetically optimised fuzzy planner
International Journal of Computational Vision and Robotics
Design of an enhanced adaptive self-organizing fuzzy sliding-mode controller for robotic systems
Expert Systems with Applications: An International Journal
Robotic path planning using hybrid genetic algorithm particle swarm optimisation
International Journal of Information and Communication Technology
A faster path planner using accelerated particle swarm optimization
Artificial Life and Robotics
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In this paper, navigation techniques for several mobile robots as many as one thousand robots using fuzzy logic are investigated in a totally unknown environment. Fuzzy logic controllers (FLC) using different membership functions are developed and used to navigate mobile robots. First a fuzzy controller has been used with four types of input members, two types of output members and three parameters each. Next two types of fuzzy controllers have been developed having same input members and output members with five parameters each. Each robot has an array of ultrasonic sensors for measuring the distances of obstacles around it and an infrared sensor for detecting the bearing of the target. These techniques have been demonstrated in various exercises, which depicts that the robots are able to avoid obstacles as well as negotiate the dead ends and reach the targets efficiently. Amongst the techniques developed, FLC having Gaussian membership function is found to be most efficient for mobile robots navigation.