Towards Aerial Embodied Intelligence: Current Status and Challenges

Unmanned Aerial Vehicle (UAV) technology is undergoing a paradigm shift from sensing platforms to Aerial Embodied Intelligence (AEI) systems capable of physical manipulation. This paper provides a structured review of this emerging field, clarifying its definition, core tasks, and current technological bottlenecks. Specifically addressing the challenges of contact-based manipulation, we analyze the dynamic coupling between aerial platforms and aerial manipulators and discuss interaction stability in unstructured environments. The implementation path of such tasks is further elucidated through a case study on UAV-based bulb replacement. Subsequently, the paper outlines future research directions, highlighting highly stable aerial platforms, dexterous manipulation, learning algorithms for intelligent adhesion, data-driven skill generalization, and the optimization of Human-Robot Interaction and multi-robot coordination as key priorities. Finally, the necessity of high-fidelity open simulation platforms is emphasized for accelerating the verification and deployment of AEI algorithms.

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Publication Details

Journal
Unmanned Systems
Published
2026-09-30
DOI
https://doi.org/10.1142/s2301385028300053
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Towards Aerial Embodied Intelligence: Current Status and Challenges

Quan Quan, Jinhui Wang
Unmanned Systems
Robot Manipulation and Learning
article

Towards Aerial Embodied Intelligence: Current Status and Challenges

Quan Quan, Jinhui Wang
article en

Abstract

Unmanned Aerial Vehicle (UAV) technology is undergoing a paradigm shift from sensing platforms to Aerial Embodied Intelligence (AEI) systems capable of physical manipulation. This paper provides a structured review of this emerging field, clarifying its definition, core tasks, and current technological bottlenecks. Specifically addressing the challenges of contact-based manipulation, we analyze the dynamic coupling between aerial platforms and aerial manipulators and discuss interaction stability in unstructured environments. The implementation path of such tasks is further elucidated through a case study on UAV-based bulb replacement. Subsequently, the paper outlines future research directions, highlighting highly stable aerial platforms, dexterous manipulation, learning algorithms for intelligent adhesion, data-driven skill generalization, and the optimization of Human-Robot Interaction and multi-robot coordination as key priorities. Finally, the necessity of high-fidelity open simulation platforms is emphasized for accelerating the verification and deployment of AEI algorithms.

Unmanned Systems
Openalex Percentile: Top 16%
Robot Manipulation and Learning
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Towards Aerial Embodied Intelligence: Current Status and Challenges — Quan Quan, Jinhui Wang · Unmanned Systems (2026) | TGRS Research Map | TGRS