论文标题
信息性的路径计划估算分位数以进行环境分析
Informative Path Planning to Estimate Quantiles for Environmental Analysis
论文作者
论文摘要
有兴趣研究自然现象的科学家通常会从环境中的位置吸收物理标本进行以后的分析。这些分析位置通常由专家启发式方法指定。取而代之的是，我们建议通过使用机器人执行内容丰富的路径计划调查来选择科学分析的位置。该调查导致与感兴趣现象的分位数相对应的位置列表。我们使用新型目标函数开发机器人规划师，以随着时间的推移提高分位数值的估计值，并找到与分位数相对应的位置的方法。我们使用先前收集的水生数据在四个不同的环境中测试我们的方法，并在现场试验中对其进行验证。与试图最大化空间覆盖率的基线方法相比，我们提出的估计分位数方法的中位误差的平均值减少了10.2％。此外，与基线相比，当将这些值定位在环境中时，在使用跨渗透性与损失函数的中位误差的平均值减少15.7％。
Scientists interested in studying natural phenomena often take physical specimens from locations in the environment for later analysis. These analysis locations are typically specified by expert heuristics. Instead, we propose to choose locations for scientific analysis by using a robot to perform an informative path planning survey. The survey results in a list of locations that correspond to the quantile values of the phenomenon of interest. We develop a robot planner using novel objective functions to improve the estimates of the quantile values over time and an approach to find locations which correspond to the quantile values. We test our approach in four different environments using previously collected aquatic data and validate it in a field trial. Our proposed approach to estimate quantiles has a 10.2% mean reduction in median error when compared to a baseline approach which attempts to maximize spatial coverage. Additionally, when localizing these values in the environment, we see a 15.7% mean reduction in median error when using cross-entropy with our loss function compared to a baseline.
