Path planning navigation of mobile robot with obstacles avoidance using fuzzy logic controller

TLDR

Autonomous mobile robots are employed in diverse fields such as manufacturing, mining, military, and transportation, where navigation requires accurate localization and obstacle detection to find collision‑free paths. The study aims to design a fuzzy logic controller for efficient obstacle avoidance and target reaching, and to present its simulation for an autonomous mobile robot. The approach uses a fuzzy logic controller that maps obstacle positions to steering commands via membership functions and an If‑Then rule base, combined with basic path‑planning strategies that adjust the robot’s heading to avoid obstacles and reach the goal. Simulation results show the robot successfully navigating around four obstacles.

Abstract

Autonomous mobile robots are used in several application areas including manufacturing, mining, military, and transportation, search and protect missions, etc. For the navigation system it is necessary to locate the position of the mobile robot in surrounding environment. For avoiding obstacles efficiently and to reach the target under many different shapes of obstacle in environment, a fuzzy logic controller has been designed to improve the movement of mobile robot according to obstacles positions by defining or establishing input variables, output variables, fuzzy logic membership functions, fuzzy logic rule base `If-Then' fuzzy inference system rules and defuzzification method. Then it has to plan a path towards desired goal. The navigation system of a mobile robot has to identify all potential obstacles in order to search for a collision free path. Obstacles avoidance and destination point can be achieved by changing the direction angle of the mobile robot. To make the mobile robot move in its environment, the basic path planning strategies have been used. While the mobile robot is navigating in its workspace environment, it avoids obstacles and look for the target. In this paper the simulation of path planning technique for an autonomous mobile robot is presented. The figure shows simulation of the mobile robot with four obstacles.