摘要
在野外灾害应急与救援过程中,受灾害或复杂地表环境的影响,快速搜索一条到达目的地的可通行性路径是一项具有挑战性的任务。近些年随着空地协同技术的不断发展,利用无人机为地面车载系统提供其周边环境的数据并搜索可通行路径成为空地协同技术研发的一个热点。本文利用机器学习方法,结合基于无人机获取的野外可见光影像自动生成的数字表面模型(DSM)对该无人机可见光影像进行了详细分类,得到了较传统方法更好的分类结果;然后基于一般性规律,建立了地表可通行性判断条件与通行速度计算公式;再通过引入分类结果以及分类的不确定性因子,对A^*算法进行了改进。基于改进的A*算法实现了实验区可通行性路径的快速搜索以及路径的可靠性评价,实验表明本文方法可得到更合理的结果。
In the process of disaster emergency and rescue, due to the impact of disaster and the complexity of the ground environment, it is a challenging task to plan a traversable route to the target place quickly. In recent years, with the rapid development of technologies in Air-ground Collaboration, using UAV to collect environmental data and plan a traversable route for the ground vehicle system has become a hot issue. In this research work, firstly, the visible images acquired by the UAV and the DSM automatically calculated from the visible images are used in Deep learning method to train a terrain surface classification model, a better result is extracted than the traditional remote sensing image classification methods;secondly, a judgement of trafficability for terrain surface based on general knowledge is established, and a formula for calculation of moving speed on different terrain surface is presented;thirdly, the classification result and its uncertainty are introduced in A^* algorithm to polish up it, then the improved A^* algorithm is used to accomplish a fast exploration of the traversable route in the experimental area, while the reliability evaluation of the route is also given as a reference for decision making in rescue process. Experiments show that our method can get more reasonable result.
作者
李修贤
孙敏
黎晓东
任翔
Li Xiuxian;Sun Min;Li Xiaodong;Ren Xiang(Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China)
出处
《石河子大学学报（自然科学版）》
CAS
北大核心
2019年第1期12-20,共9页
Journal of Shihezi University(Natural Science)
基金
新疆兵团重大项目(2017DB005)
新疆兵团重点领域创新团队计划项目(2016BD001)
关键词
空地协同
路径搜索
A^*算法
应急救援
Air-ground collaborative
exploration of the traversable route
A^* algorithm
disaster emergency and rescue
