山地搜索的地形信息无人机路径规划:基于斜坡的概率方法
Xi Wang1, Xing Wang1, Pengliang Zhao1
1The School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411100, China.
Sensors (Basel, Switzerland)
|January 10, 2026
概括
本研究介绍了一种斜率概率搜索 (SPS) 算法,用于使用无人机 (UAV) 在山区定位失踪人员. 创新的算法显著提高了在具有挑战性的地形中搜索效率和成功率.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 搜索和救援行动 搜索和救援行动
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 在复杂的山区地形中寻找失踪人员存在重大挑战.
- 使用无人机 (UAV) 的传统搜索方法通常依赖于详尽的覆盖模式,这可能是低效的.
- 失踪人员的动态行为使搜索工作复杂化.
研究的目的:
- 开发一种创新的算法,以提高在复杂的山地地形中寻找动态失踪人员的效率.
- 将无人机搜索模式从覆盖模式转变为智能,指导式探索.
- 为下一代智能搜救系统提供理论基础和实践框架.
主要方法:
- 引入基于修改的A*框架的斜率概率搜索 (SPS) 算法.
- 构建一个动态的全球概率地图,将地形斜率与失踪者的行为联系起来.
- 为失踪人员设计了三个动态模型:受地形限制,遵循路径和随机步行.
- 利用一个独特的启发式功能来平衡开发和勘探.
主要成果:
- 在模拟实验中,SPS算法的成功率为88.9%.
- 平均搜索时间远低于传统方法.
- 即使在有限的搜索时间和传感器范围的严重限制下,也显示出有效性.
结论:
- 在复杂的地形中,SPS算法可显著提高失踪人员的搜索效率.
- 开发的算法为智能搜索和救援系统提供了一个实用的框架.
- 这项研究为未来自主搜救技术的进步奠定了基础.
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