Navigation of Autonomous Mobile Robot Using Adaptive Neuro-Fuzzy Controller

  • Prases Kumar Mohanty
  • Dayal R. Parhi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


This paper presents a new sensor-based technique for autonomous mobile robot navigation in uncertain environments. In recent day, computational intelligent techniques, such as artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro-fuzzy inference system (ANFIS), are mainly considered as applicable techniques from modeling point of view. ANFIS has taken the integrate performance of neural network and fuzzy inference system. In this architecture, different obstacle range data, such as front obstacle distance (FOD), left obstacle distance (LOD), right obstacle distance (ROD), and heading angle (HA) from each ultrasonic range finders, are given as input to the adaptive fuzzy controller and output from the controller is steering angle for the mobile robot. Simulation experiments using MATLAB demonstrate that the proposed ANFIS navigational controller can be effectively applied to navigate the mobile robot safely in unknown environments and reach to target objects.


Adaptive neuro-fuzzy inference system Mobile robot Navigation Obstacle avoidance 


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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringNational Institute of TechnologyRourkelaIndia

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