WA-LPA*: An Energy-Aware Path-Planning Algorithm for UAVs in Dynamic Wind Environments

Energy optimization is crucial for unmanned aerial vehicle (UAV) path planning, particularly in complex wind-field environments. Most existing path-planning algorithms rely on simplified energy consumption models, which often fail to adequately capture the effects of wind fields. To address this limitation, a wind-adaptive lifelong planning A* algorithm (WA-LPA*) is proposed for energy-aware path planning in dynamic wind environments. WA-LPA* constructs a composite heuristic function incorporating wind-field alignment factors and integrates a hierarchical height-aware optimization strategy. Meanwhile, an adaptive replanning mechanism is designed based on the change characteristics of the wind field. Simulation experiments conducted across representative scenarios demonstrate that, compared to conventional algorithms that neglect wind-field effects, WA-LPA* achieves energy efficiency improvements of 5.9–29.4%.

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Publication Details

Journal
Drones
Published
2025-12-11
DOI
https://doi.org/10.3390/drones9120850
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

WA-LPA*: An Energy-Aware Path-Planning Algorithm for UAVs in Dynamic Wind Environments

Bangjie Li, Hongwei Zhu, Qisong Yang, Desong Du et al.
Drones
Robotic Path Planning Algorithms
article

WA-LPA*: An Energy-Aware Path-Planning Algorithm for UAVs in Dynamic Wind Environments

Bangjie Li, Hongwei Zhu, Qisong Yang, Desong Du, Fangjia Lian
article en

Abstract

Energy optimization is crucial for unmanned aerial vehicle (UAV) path planning, particularly in complex wind-field environments. Most existing path-planning algorithms rely on simplified energy consumption models, which often fail to adequately capture the effects of wind fields. To address this limitation, a wind-adaptive lifelong planning A* algorithm (WA-LPA*) is proposed for energy-aware path planning in dynamic wind environments. WA-LPA* constructs a composite heuristic function incorporating wind-field alignment factors and integrates a hierarchical height-aware optimization strategy. Meanwhile, an adaptive replanning mechanism is designed based on the change characteristics of the wind field. Simulation experiments conducted across representative scenarios demonstrate that, compared to conventional algorithms that neglect wind-field effects, WA-LPA* achieves energy efficiency improvements of 5.9–29.4%.

DronesVol. 9(12)
Harbin Institute of Technology (CN), PLA Rocket Force University of Engineering (CN)
Openalex Percentile: Top 59%
Robotic Path Planning Algorithms
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