Work

A Survey on the Key Technologies of UAV Motion Planning

Year: 2025

Type: article

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.

Source: Drones

DOI: 10.3390/drones9030194

Authors: Yuquan Zhou, Li Yan, Yaxi Han, Hong Xie, Yinghao Zhao

Institutions: Wuhan University, PLA Information Engineering University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: National Natural Science Foundation of China