Comparative Evaluation of Reinforcement Learning Algorithms for Multi-Agent Unmanned Aerial Vehicle Path Planning in 2D and 3D Environments

Comparative Evaluation of Reinforcement Learning Algorithms for Multi-Agent Unmanned Aerial Vehicle Path Planning in 2D and 3D Environments

Path planning in multi-agent UAV swarms is a crucial issue that involves avoiding collisions in dynamic, obstacle-filled environments while consuming the least amount of time and energy possible. This work comprehensively evaluates reinforcement learning (RL) algorithms for multi-agent UAV path plan...

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Bibliographic Details
Main Authors: Mirza Aqib Ali, Adnan Maqsood, Usama Athar, Hasan Raza Khanzada
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Drones
Subjects:
multi-agent systems
UAV swarms
path planning
reinforcement learning
autonomous systems
UAV navigation
Online Access:https://www.mdpi.com/2504-446X/9/6/438
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