基于极坐标的差分进化算法用于无人机视觉传感器移动目标搜索
Polar Coordinate-based Differential Evolution for Moving Target Search Using Vision Sensor on Unmanned Aerial Vehicles
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中文总结 AI 辅助
针对无人机搜索救援，提出基于极坐标的差分进化算法，先建模目标动态与检测似然性，导出适应度函数，再用该算法生成搜索路径，经模拟和实际实验评估，其在检测概率和执行时间上优于现有算法，适用于实际应用。
中文摘要 AI 辅助
在搜索救援行动中，存在“黄金时间”，此时找到存活目标概率最高。本文旨在为无人机提出新搜索算法，提高检测概率与执行时间。先将目标动态建模为马尔可夫过程，检测似然性建模为图像质量和观察者视觉的函数，用贝叶斯理论导出适应度函数。接着引入基于极坐标的差分进化算法（PDE）生成搜索路径最大化适应度函数。PDE利用极坐标纳入无人机运动学约束和机动特性。通过模拟、对比分析及实际无人机实验评估算法性能，结果表明PDE算法在不同搜索场景下检测概率和执行时间优于现有算法且适用于实际应用，算法源代码可获取。
英文摘要
In search and rescue operations, there is a period known as the "golden time" during which the probability of finding the target alive is highest. The objective of this work is to propose a new search algorithm for unmanned aerial vehicles (UAVs) with a focus on improving the detection probability and execution time. We approach this problem by first modeling target dynamics as a Markov process and the detection likelihood as a function of image quality and the observer's vision. We then employ Bayesian theory to derive a fitness function representing the probability distribution of the target's location over the search area. Finally, we introduce a new algorithm named polar coordinate-based differential evolution (PDE) to generate a UAV search path that maximizes this fitness function. The PDE algorithm utilizes polar coordinates to incorporate kinematic constraints and maneuver properties of the UAV, allowing for better exploration of the solution space. A series of simulations and comparative analyses have been conducted to evaluate the performance of the proposed algorithm. Experiments involving a real UAV have also been conducted. Results demonstrate that the PDE algorithm outperforms state-of-the-art algorithms in terms of detection probability and execution time across diverse search scenarios while remaining practical for real-world applications. The source code of the algorithm is available at https://github.com/thuhangkhuat/PDE_target_search.
发表机构
- Ulsan National Institute of Science and Technology（蔚山国立科学技术院）
- VinUniversity（文大大学）
机构由 AI 辅助整理，请以论文原文为准。
