Environmental-Aware UAV Path Planning for Maritime Search and Rescue
Daoshun Xie, Shenhua Yang, Weijun Wang, Zongyue Wang · 2025
As global trade expands, maritime transportation faces increasing risks from frequent accidents, underscoring the urgent need for improved search and rescue operations. This paper introduces an innovative UAV-based maritime search and rescue (SAR) route planning method that integrates dynamic environmental factors such as sea winds and ocean currents, which directly influence the position of search and rescue targets. Inspired by convolutional techniques and employing a gridbased model, this method optimizes UAV search paths to adapt to environmental changes, thereby enhancing search efficiency and reliability. This strategy not only improves operational efficiency in complex maritime areas but also significantly reduces associated risks and costs. The code is available at https://github.com/cooking43/SAR.