Kriging-based robotic exploration for soil moisture mapping using a cosmic-ray sensor
Kriging-based robotic exploration for soil moisture mapping using a cosmic-ray sensor
复制标题
使用宇宙射线传感器进行基于克里金法的土壤湿度测绘机器人探索
DOI：
10.1002/rob.21914
复制
发表时间：
2019
影响因子：
8.3
通讯作者：
Pulido Fentanes J
中科院分区：
文献类型：
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作者：
Pulido Fentanes J
土壤水分监测是提高农业生产效益和保护环境的重要环节。测量土壤含水量的传统方法费力且昂贵，因此人们对开发可以减少工作量和成本的传感器和技术的兴趣越来越大。在这项工作中，我们建议使用一个自主的移动的机器人配备了一个国家的最先进的非接触式土壤水分传感器建设水分地图上飞，并自动选择最佳的采样位置。我们引入了一个自主的勘探策略，由土壤水分模型的质量驱动，指示信息不太精确的领域。传感器模型遵循泊松分布，我们演示了如何将这些测量到克里格框架。我们还调查了一系列不同的勘探策略，并通过一组评估实验的基础上收集的两个不同领域的真实的土壤水分数据，评估其有用性。我们展示了使用自适应测量间隔和自适应采样策略构建更高质量的土壤水分模型的好处。所提出的方法是通用的，可以应用到其他场景中的测量现象直接影响采集时间，需要空间映射。
Soil moisture monitoring is a fundamental process to enhance agricultural outcomes and to protect the environment. The traditional methods for measuring moisture content in the soil are laborious and expensive, and therefore there is a growing interest in developing sensors and technologies which can reduce the effort and costs. In this work, we propose to use an autonomous mobile robot equipped with a state‐of‐the‐art noncontact soil moisture sensor building moisture maps on the fly and automatically selecting the most optimal sampling locations. We introduce an autonomous exploration strategy driven by the quality of the soil moisture model indicating areas of the field where the information is less precise. The sensor model follows the Poisson distribution and we demonstrate how to integrate such measurements into the kriging framework. We also investigate a range of different exploration strategies and assess their usefulness through a set of evaluation experiments based on real soil moisture data collected from two different fields. We demonstrate the benefits of using the adaptive measurement interval and adaptive sampling strategies for building better quality soil moisture models. The presented method is general and can be applied to other scenarios where the measured phenomena directly affect the acquisition time and need to be spatially mapped.