基于概率扩散模型的动态无人机落水人员搜索作业
Dynamic UAV-based search operations using probabilistic diffusion modeling of Man Overboard incident victims
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中文总结 AI 辅助
该研究针对游轮落水人员搜救难题，提出结合扩展卡尔曼滤波与漂移模型的区域预测方法，评估五种无人机搜索策略，其中改进概率引导搜索法在延迟20分钟、检测成功率30%时平均搜救成功率超80%。
中文摘要 AI 辅助
2010至2019年期间，超过70%从游轮落水的人员不幸丧生。本文提出一种可靠预测落水人员所在区域的策略，并详细描述利用无人机技术寻找该人员的搜索方法。该搜索区域预测方法采用扩展卡尔曼滤波，结合漂移模型（Leeway model）的信息，同时考虑人员运动的不确定性及该区域的天气状况，以追踪海上失踪人员。随后，无人机利用该信息搜索人员。本文提出并评估了五种在该动态区域搜索的方法：锯齿法（Zigzag）、往返法（Boustrophedon）、螺旋法（Spiral）、概率引导搜索法（Probability Informed Search）及改进概率引导搜索法（Improved Probability Informed Search, IPIS）。即使无人机在落水事件发生20分钟后才启动搜索任务，且假设检测方法的成功率仅为30%，IPIS方法寻找人员的平均成功率仍超过80%。所有模拟环境及方法评估的代码均已发布在GitHub页面，链接为this https URL。
英文摘要
More than 70% of the people that fell overboard cruise ships in the period 2010-2019 lost their lives. This paper presents a strategy for reliably predicting the area a person may be in after a man overboard incident, and describes in detail the search methods to find them utilizing UAV technology. The search area prediction method employs an Extended Kalman Filter that capitalizes on the information from the Leeway model to track the missing person in the sea by taking into account the uncertainty of the movement of the person and the weather conditions in the area. Then, a UAV uses this information to search for the person. Five different methods for searching in this dynamic area are presented and evaluated - the Zigzag, the Boustrophedon, the Spiral, the Probability Informed Search and the Improved Probability Informed Search (IPIS) methods. The IPIS method provides success rate of over 80% on average for finding a person, even if the UAV initiates the search mission 20 minutes after the man overboard incident and even assuming a detection method with a success rate of 30%. All code for the simulation environment and the evaluation of the methods is available on our GitHub page at https://github.com/diangeli/pdms-man-overboard.
发表机构
- Technical University of Denmark（丹麦技术大学）
机构由 AI 辅助整理，请以论文原文为准。
