A Survey on the Key Technologies of UAV Motion Planning

Unmanned aerial vehicles (UAVs) are widely employed across diverse fields due to their flexibility and scalability. However, achieving full autonomy remains a challenge as human intervention is still required in most scenarios. Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. This paper provides a comprehensive overview of UAV motion planning frameworks, systematically addressing three key components: map representation, path planning, and trajectory optimization. Map representation establishes environmental awareness, path planning balances efficiency and safety in path generation, and trajectory optimization refines paths into feasible, energy-efficient motions. Unlike prior reviews focused on specific techniques, this study offers an integrated perspective, helping researchers understand the overall framework and recent advancements in UAV motion planning. Additionally, emerging trends and potential strategies are discussed to improve the efficiency, adaptability, and robustness of UAVs to meet increasingly complex mission requirements.

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Institutions

Publication Details

Journal
Drones
Published
2025-03-06
DOI
https://doi.org/10.3390/drones9030194
Citations
9
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
11.48

Funders

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article

A Survey on the Key Technologies of UAV Motion Planning

Yinghao Zhao, Hong Xie, Yaxi Han, Yuquan Zhou et al.
9 citations
Drones
Robotic Path Planning Algorithms
11.48
article

A Survey on the Key Technologies of UAV Motion Planning

Yinghao Zhao, Hong Xie, Yaxi Han, Yuquan Zhou, Li Yan
article en
9 citations

Abstract

Unmanned aerial vehicles (UAVs) are widely employed across diverse fields due to their flexibility and scalability. However, achieving full autonomy remains a challenge as human intervention is still required in most scenarios. Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. This paper provides a comprehensive overview of UAV motion planning frameworks, systematically addressing three key components: map representation, path planning, and trajectory optimization. Map representation establishes environmental awareness, path planning balances efficiency and safety in path generation, and trajectory optimization refines paths into feasible, energy-efficient motions. Unlike prior reviews focused on specific techniques, this study offers an integrated perspective, helping researchers understand the overall framework and recent advancements in UAV motion planning. Additionally, emerging trends and potential strategies are discussed to improve the efficiency, adaptability, and robustness of UAVs to meet increasingly complex mission requirements.

DronesVol. 9(3)
PLA Information Engineering University (CN), Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Robotic Path Planning Algorithms
11.48
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