Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Area of Science:

• Computer Science
• Robotics
• Artificial Intelligence

Background:

• Unmanned aerial vehicles (UAVs) offer flexible network deployment but face challenges in throughput, delay, cost, and energy.
• Path planning is critical for efficient UAV communication networks.

Purpose of the Study:

• To investigate and survey bio-inspired algorithms for UAV path planning over the last decade.
• To provide a comprehensive review of existing bio-inspired algorithms for UAV path planning, a topic not yet extensively covered.

Main Methods:

• Literature review focusing on bio-inspired optimization algorithms applied to UAV path planning.
• Analysis of algorithms based on key features, working principles, advantages, and limitations.
• Comparative study of path planning algorithms based on performance factors.

Main Results:

• Identified and analyzed prevailing bio-inspired algorithms for UAV path planning.
• Compared various algorithms based on their characteristics and performance.
• Summarized current challenges and future research directions in the field.

Conclusions:

• Bio-inspired algorithms show significant potential for solving complex UAV path planning problems with nonlinear constraints.
• This survey provides a foundational resource for understanding and advancing bio-inspired UAV path planning techniques.
• Future research should focus on addressing identified challenges and exploring emerging trends in UAV path planning.