mlsanityData to 14 Oct 2026

Autonomous Unmanned Aerial Vehicle Navigation using Reinforcement Learning: A Systematic Review

arXiv 2208.12328 ↗First posted 25 Aug 2022cs.RO cs.AIcited by 6

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Abstract (arXiv)

There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones, in different applications such as packages delivery, traffic monitoring, search and rescue operations, and military combat engagements. In all of these applications, the UAV is used to navigate the environment autonomously - without human interaction, perform specific tasks and avoid obstacles. Autonomous UAV navigation is commonly accomplished using Reinforcement Learning (RL), where agents act as experts in a domain to navigate the environment while avoiding obstacles. Understanding the navigation environment and algorithmic limitations plays an essential role in choosing the appropriate RL algorithm to solve the navigation problem effectively. Consequently, this study first identifies the main UAV navigation tasks and discusses navigation frameworks and simulation software. Next, RL algorithms are classified and discussed based on the environment, algorithm characteristics, abilities, and applications in different UAV navigation problems, which will help the practitioners and researchers select the appropriate RL algorithms for their UAV navigation use cases. Moreover, identified gaps and opportunities will drive UAV navigation research.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 54 of its 158 references that are in the map. First posted on arXiv 25 Aug 2022.

Builds on

54 of 158 references.

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50 most cited of 54 All 54 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 2; 2026: 1.

6 papers.

  1. 2023Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directionscited by 21
  2. 2023Recent Advancements in Deep Learning Applications and Methods for Autonomous Navigation: A Comprehensive Reviewcited by 6
  3. 2025Deep RL-based Autonomous Navigation of Micro Aerial Vehicles (MAVs) in a complex GPS-denied Indoor Environmentcited by 1
  4. 2025Autonomous UAV Flight Navigation in Confined Spaces: A Reinforcement Learning Approachcited by 1
  5. 2024On-policy Actor-Critic Reinforcement Learning for Multi-UAV Explorationcited by 0
  6. 2026UAV Trajectory Optimization via Improved Noisy Deep Q-Networkcited by 0