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An in-depth analysis of UAV path planning, including procedures, algorithms, optimization models, and emerging

Muhammad Nafees1, Tamkeen Syeda1, Amjad Ali1

  • 1Computer Science & IT, Karachi Institute of Economics and Technology, Karachi Sindh, Pakistan.

Methodsx
|March 11, 2026
PubMed
Summary

This study reviews Unmanned Aerial Vehicle (UAV) path planning techniques, covering algorithms and models. It highlights AI-driven methods and future challenges for robust navigation systems.

Keywords:
Multi-UAV coordinationOptimization algorithmsProblem modelsUAV path planningUnmanned aerial vehicles (UAVs)

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Area of Science:

  • Robotics and Autonomous Systems
  • Artificial Intelligence
  • Aerospace Engineering

Background:

  • Unmanned Aerial Vehicles (UAVs) are crucial for surveillance, environmental monitoring, and delivery.
  • Effective path planning is essential for autonomous UAV navigation in complex environments.

Purpose of the Study:

  • To provide a comprehensive overview of UAV path planning research.
  • To analyze various algorithms, problem models, and emerging challenges in UAV navigation.

Main Methods:

  • Classification of UAV path planning techniques.
  • Review of heuristic, metaheuristic, and AI-driven algorithms.
  • Assessment of algorithm strengths, weaknesses, and problem models.

Main Results:

  • Detailed analysis of traditional, hybrid, and AI-driven path planning approaches.
  • Identification of key challenges including real-time processing and multi-UAV coordination.
  • Evaluation of algorithm performance for diverse applications.

Conclusions:

  • UAV path planning is a dynamic field with significant advancements.
  • Future research should focus on scalability, real-time adaptation, and energy efficiency.
  • This review aids researchers in developing advanced UAV navigation systems.