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This review aims to clarify the roles of reinforcement learning in UAV control and identify future research avenues for real-world applications.

June 10, 2026DronesOpen Access

A Review of Reinforcement Learning for Multirotor UAVs from a Hierarchical Control Perspective: Biomimetic Architecture and Sim-to-Real

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Review analyzes reinforcement learning roles in hierarchical UAV control, highlighting future research directions.

This review aims to clarify the roles of reinforcement learning in UAV control and identify future research avenues for real-world applications.
Review of existing literature on reinforcement learning and UAV control systems.
Categorization of RL studies into low, mid, and high-level control functions based on a proposed hierarchical framework.
Emphasis on sim-to-real challenges and the functional roles of RL policies in the control architecture.
Established a hierarchy of UAV control roles for RL: dynamic stabilization, perception-action coordination, and task planning.
Identified gaps in understanding the relationship between RL algorithm characteristics and control requirements.
Outlined future research directions for enhancing real-world deployment of RL in UAV systems.

Wei et al. (2026) studied this question.

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June 10, 2026DronesOpen Access

View Full Paper

Ask AI

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Authors

Review analyzes reinforcement learning roles in hierarchical UAV control, highlighting future research directions.

This review aims to clarify the roles of reinforcement learning in UAV control and identify future research avenues for real-world applications.
Review of existing literature on reinforcement learning and UAV control systems.
Categorization of RL studies into low, mid, and high-level control functions based on a proposed hierarchical framework.
Emphasis on sim-to-real challenges and the functional roles of RL policies in the control architecture.
Established a hierarchy of UAV control roles for RL: dynamic stabilization, perception-action coordination, and task planning.
Identified gaps in understanding the relationship between RL algorithm characteristics and control requirements.
Outlined future research directions for enhancing real-world deployment of RL in UAV systems.

Wei et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark