论文标题
使用卫星图像进行ASV导航的随机计划
Stochastic Planning for ASV Navigation Using Satellite Images
论文作者
论文摘要
自主表面容器（ASV）代表了自动化湖泊水质监测的有前途的技术。在这项工作中，我们将卫星图像用作粗图，并计划机器人的采样路线。但是，卫星图像与实际湖泊之间的不一致以及环境干扰（例如风，水生植被和不断变化的水位）可能会使机器人难以参观先前地图建议的地方。本文提出了一种强大的路线规划算法，鉴于这些环境干扰，该算法可最大程度地减少预期的总行驶距离，从而引起地图中的不确定性。我们验证了算法在一千多个加拿大湖泊中的模拟中的功效，并在加拿大安大略省北部的一个湖泊中展示了我们算法的应用。视频可在我们的网站https://pcctp.github.io/上找到。
Autonomous surface vessels (ASV) represent a promising technology to automate water-quality monitoring of lakes. In this work, we use satellite images as a coarse map and plan sampling routes for the robot. However, inconsistency between the satellite images and the actual lake, as well as environmental disturbances such as wind, aquatic vegetation, and changing water levels can make it difficult for robots to visit places suggested by the prior map. This paper presents a robust route-planning algorithm that minimizes the expected total travel distance given these environmental disturbances, which induce uncertainties in the map. We verify the efficacy of our algorithm in simulations of over a thousand Canadian lakes and demonstrate an application of our algorithm in a 3.7 km-long real-world robot experiment on a lake in Northern Ontario, Canada. Videos are available on our website https://pcctp.github.io/.
