期刊
IEEE TRANSACTIONS ON ROBOTICS
卷 32, 期 6, 页码 1498-1511出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2016.2603528
关键词
Agriculture; path planning; robot sensing systems
类别
资金
- National Science Foundation [1111638, 0917676, 1566247]
- Minnesota Discovery, Research and InnoVation Economy Robotics, Sensors, and Advanced Manufacturing initiative
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1111638] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0917676, 1566247] Funding Source: National Science Foundation
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.
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