Lian, Fangjia (Rocket Force University of Engineering), Yang, Qisong (Delft University of Technology), li, bangjie (Rocket Force University of Engineering), wang, Pengxiang (Computer Science), LUO, Haoqi (Harbin Institute of Technology), du, Desong (Harbin Institute of Technology)

Optimal Path Planning of Unmanned Aerial Vehicle with Wind Field

Scheduled for presentation during the Video Session "On-Demand Video Presentations" (VP-VP), Saturday, November 22, 2025, 08:00−18:00, On-Demand Platform

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on April 2, 2026

Abstract

This paper proposes a novel A* algorithm for unmanned aerial vehicles (UAVs) path planning that integrates wind field dynamics into the energy optimization process. First, based on the dynamics model, an energy consumption model is established to characterize the effects of wind during trajectory tracking tasks. Building upon this, we introduce a wind-augmented A* algorithm that dynamically adjusts its heuristic estimates based on real-time energy cost predictions influenced by local wind conditions. This enables UAVs to strategically exploit favorable winds and mitigate adverse flows, achieving energy-efficient navigation. Numerical experiments in composite wind field demonstrate that the proposed method reduces energy consumption by an average of approximately 6% compared to conventional A* algorithms, validating its effectiveness for intelligent UAVs operations in complex atmospheric environments.