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Three-Dimensional Force System:Problem Solving01:30

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Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

Marwah Almasri1, Khaled Elleithy2, Abrar Alajlan3

  • 1Computer Science and Engineering Department, University of Bridgeport, 126 Park Ave, Bridgeport, CT 06604, USA. maalmasr@my.bridgeport.edu.

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Summary
This summary is machine-generated.

This study introduces a fuzzy logic fusion model for autonomous mobile robot navigation, enhancing sensor reliability for collision-free movement and path following. The system effectively integrates multiple sensors to improve robot performance in complex environments.

Keywords:
autonomous mobile robotscollision avoidancefusionfuzzy logicpath following

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Sensor Fusion

Background:

  • Autonomous mobile robots rely on sensors like GPS and cameras, which can be prone to failure and inaccurate readings.
  • Sensor fusion is crucial for overcoming individual sensor limitations and improving overall robot performance.
  • Existing navigation systems often struggle with reliability in dynamic environments.

Purpose of the Study:

  • To develop a collision-free autonomous mobile robot navigation system.
  • To enhance robot navigation performance through a fuzzy logic sensor fusion model.
  • To integrate collision avoidance and line-following capabilities in a single robotic system.

Main Methods:

  • A fuzzy logic fusion model was designed with nine inputs (eight distance sensors and one camera) and two outputs (wheel velocities).
  • The system utilizes 24 fuzzy rules for robot movement, incorporating collision avoidance and line-following.
  • The Webots Pro simulator was used for environment and robot modeling, followed by real-time experiments.

Main Results:

  • The proposed fuzzy logic fusion model successfully enabled collision-free navigation for the mobile robot.
  • The system demonstrated effective line or path following using three ground sensors.
  • Simulations and real-time experiments validated the methodology with static and dynamic obstacles, and multi-robot scenarios.

Conclusions:

  • Fuzzy logic sensor fusion significantly enhances the reliability and performance of autonomous mobile robot navigation.
  • The integrated approach of collision avoidance and line following is feasible and effective.
  • The developed system provides a robust solution for complex robotic navigation tasks.