Sensor Planning for a Symbiotic UAV and UGV System for Precision Agriculture
Sensor Planning for a Symbiotic UAV and UGV System for Precision Agriculture
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DOI：
10.1109/tro.2016.2603528
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发表时间：
2016-12-01
影响因子：
7.8
通讯作者：
Isler, Volkan
中科院分区：
文献类型：
--
作者：
Tokekar, Pratap;Hook, Joshua Vander;Isler, Volkan
我们研究了两个新的信息丰富的路径规划问题，这些问题是由精准农业中空中和地面机器人的使用所引发的。第一个问题，被称为带邻域的采样旅行商问题（SAMPLINGTSPN），是由无人驾驶地面车辆（UGV）用于获取耗时的土壤测量的场景所引发的。SAMPLINGTSPN的输入是一组可能重叠的圆盘。目标是在每个圆盘中选择一个采样位置，并规划一条路径来访问这些采样位置，以使旅行时间和测量时间之和最小。第二个问题涉及使用能量有限的无人驾驶飞行器（UAV）获取最大数量的空中测量值。我们研究了两种类型的机器人形成共生系统的场景——UAV降落在UGV上，并且UGV在部署地点之间运输UAV。本文做出了以下贡献。首先，我们为SAMPLINGTSPN提出了一种$O(r_{max} / r_{min})$近似算法，其中$r_{min}$和$r_{max}$是输入圆盘的最小和最大半径。其次，我们展示了如何使用度量图对UAV规划问题进行建模，并制定了一个定向越野实例，可对其应用一种已知的近似算法。第三，我们将这两种算法应用于获取地面和空中测量值的问题，以便准确估计一块土地的氮含量图。除了理论结果，我们还展示了使用真实土壤数据进行模拟以及UAV初步田间实验的结果。
We study two new informative path planning problems that are motivated by the use of aerial and ground robots in precision agriculture. The first problem, termed sampling traveling salesperson problem with neighborhoods (SAMPLINGTSPN), is motivated by scenarios in which unmanned ground vehicles (UGVs) are used to obtain time-consuming soil measurements. The input in SAMPLINGTSPN is a set of possibly overlapping disks. The objective is to choose a sampling location in each disk and a tour to visit the set of sampling locations so as to minimize the sum of the travel and measurement times. The second problem concerns obtaining the maximum number of aerial measurements using an unmanned aerial vehicle (UAV) with limited energy. We study the scenario in which the two types of robots form a symbiotic system-the UAV lands on the UGV, and the UGV transports the UAV between deployment locations. This paper makes the following contributions. First, we present an O(r(max)/r(min)) approximation algorithm for SAMPLINGTSPN, where r(min) and r(max) are the minimum and maximum radii of input disks. Second, we show how to model the UAV planning problem using a metric graph and formulate an orienteering instance to which a known approximation algorithm can be applied. Third, we apply the two algorithms to the problem of obtaining ground and aerial measurements in order to accurately estimate a nitrogen map of a plot. Along with theoretical results, we present results from simulations conducted using real soil data and preliminary field experiments with the UAV.