Navigation and obstacle avoidance are the most important task for any mobile robots. This
article presents the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for mobile …

Purpose This paper aims to design and implement the multiple adaptive neuro-fuzzy
inference system (MANFIS) architecture-based sensor-actuator (motor) control technique for …

In recent years, the interest in research on robots has increased extensively; mainly due to
avoid human to involve in hazardous task, automation of Industries, Defence, Medical and …

The motion control problem of an autonomous wheeled mobile robot has been widely
investigated in the past two decades. In this article, the minimum rule based Adaptive Neuro …

Autonomous navigation of a mobile robot in an unknown environment with highly cluttered
obstacles is a fundamental issue in mobile robotics research. We propose an adaptive …

Navigation and obstacle avoidance in an unknown environment is proposed in this paper
using hybrid neural network with fuzzy logic controller. The overall system is termed as …

In the present work, autonomous mobile robot (AMR) system is intended with basic
behaviour, one is obstacle avoidance and the other is target seeking in various …

This article focuses on the navigational path analysis of mobile robots using the adaptive
neuro-fuzzy inference system (ANFIS) in a cluttered dynamic environment. In the ANFIS …

This article proposes an adaptive neuro-fuzzy inference system (ANFIS) for solving
navigation problems of an autonomous ground vehicle (AGV). The system consists of four …

In recent years intelligent soft computing techniques such as fuzzy inference system (FIS),
artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are …