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논문 기본 정보

자료유형
학술저널
저자정보
Lei Li (Henan Vocational University of Science and Technology) Huimin Peng (Henan Vocational University of Science and Technology) Xingxue Ren (Henan Vocational University of Science and Technology) Qianqian Wang (Henan Vocational University of Science and Technology)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.14 No.2
발행연도
2025.4
수록면
257 - 267 (11page)
DOI
10.5573/IEIESPC.2025.14.2.257

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초록· 키워드

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Drones have shown enormous potential in urban logistics due to their efficiency and flexibility. However, traditional path planning methods such as particle swarm optimization and A* algorithm often find it difficult to meet both efficiency and safety when used alone. Therefore, this study proposes a new unmanned aerial vehicle logistics distribution path planning method. By adjusting parameters and optimizing search strategies, the particle swarm optimization algorithm utilizes the efficient pathfinding ability of A* algorithm to ensure its security. The results show that the obstacle avoidance success rate of the model is 94.85%, which is the best performance compared to other comparative algorithms and provides the shortest and smoothest path selection. This method demonstrates good path planning efficiency and stability, improving logistics and distribution capabilities in urban environments. This provides valuable reference for intelligent path planning and intelligent transportation systems.

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Abstract
1. Introduction
2. Related Work
3. UAV Path Planning Model Construction Based on Improved PSO and A* Algorithms
4. Result Analysis of UAV Path Planning Model Based on Improved PSO and A* Algorithms
5. Conclusion
References

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