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Enhanced QoS Routing Protocol for an Unmanned Ground Vehicle, Based on the ACO Approach.

Ali M Ali1, Md Asri Ngadi1, Rohana Sham2

  • 1Department of Computer Science, Faculty of Computing, University Technology Malaysia, Johor Bahru 81310, Malaysia.

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Summary
This summary is machine-generated.

This study enhances firefighting unmanned ground vehicle networks using ant colony optimization for efficient routing. The improved system ensures faster navigation to fires, avoiding traffic issues in crowded urban environments.

Keywords:
ACOQoSRSV2XVANETfirefighting UGV

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Area of Science:

  • Robotics and Autonomous Systems
  • Network Engineering
  • Artificial Intelligence

Background:

  • Managing networks for firefighting unmanned ground vehicles (UGVs) in crowded areas presents significant challenges.
  • Network peculiarities include large coverage areas, frequent connection failures, and dynamic topology changes.

Purpose of the Study:

  • To enhance the communication network and navigation capabilities of self-driving firefighting UGVs.
  • To determine optimal routing tracks to fire locations, improving response efficiency.

Main Methods:

  • Implementation of a novel recommendation system (RS) model.
  • Application of the ant colony optimization (ACO) technique, a swarm intelligence method.
  • Focus on improving routing algorithms for vehicles ad-hoc networks (VANETs).

Main Results:

  • The proposed model significantly enhances the navigation of firefighting UGVs towards fire regions.
  • Achieved shortest possible routes, effectively avoiding closed roads and traffic accidents.
  • Demonstrated improved performance in dynamic and challenging network conditions.

Conclusions:

  • The ant colony optimization-based model offers a robust solution for managing firefighting UGV networks.
  • This research contributes to the control and management of ad-hoc vehicle networks, V2X communication, and the Internet of Things (IoT).
  • The findings support more effective and safer deployment of autonomous systems in emergency response scenarios.