Development of Informative Path Planning for Inspection of the Hanford Tank Farm
Development of Informative Path Planning for Inspection of the Hanford Tank Farm
复制标题
开发用于检查汉福德罐区的信息路径规划
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Y. T. Tan
中科院分区：
文献类型：
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作者：
S. Zanlongo;Leonardo Bobadilla;D. McDaniel;Y. T. Tan
传统的环境和结构监测通常使用部署在预定位置的静态传感器网络或使用光栅技术进行区域覆盖的移动机器人。这些方法依赖于操作人员对被测量的未知场的性质进行假设，并且对于定位感兴趣的区域通常非常耗时。在这里，我们的目标是迅速定位汉福德核电站高放核废料罐可能发生的泄漏。这些储罐的结构排除了大多数传感器网络方法，并提出了机器人检查的许多问题，例如在高度受限的环境中导航。这项工作使用贝叶斯优化方法来指导移动机器人的搜索策略，并实现了一个实用函数，该函数允许在选择未来搜索位置时将结构的先验知识纳入其中。与传统的穷举方法相比，我们的方法可以快速减小RMSE误差，缩短机器人必须移动的距离。
Traditional environmental and structural monitoring often uses static sensor networks deployed at predetermined locations or mobile robots that use a rastering technique for area coverage. These methods rely on the operators making assumptions about the nature of the unknown field that is being measured and are often time-consuming for localizing an area of interest. Here, we aim to quickly localize possible leaks within high-level nuclear waste tanks at the Hanford facility. The structure of these tanks precludes most sensor network approaches and raises many issues with robotic inspection, such as navigation within highly constrained environments. This work uses a Bayesian Optimization approach for guiding a mobile robot’s search strategy and implements a utility function that allows for prior knowledge of the structure to be incorporated when selecting future search locations. Compared to traditional exhaustive approaches, our method quickly reduces RMSE error and shortens the distance the robot must travel.