单机器人线路覆盖问题:理论、算法和实验

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Networks Pub Date : 2023-07-25 DOI:10.1002/net.22171
Saurav Agarwal, Srinivas Akella
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引用次数: 0

摘要

行覆盖是为环境中给定的一组一维特征提供服务的任务。它对线性基础设施的检查很重要,如道路网络、电力线、石油和天然气管道。本文通过将空中和地面机器人的单机器人线路覆盖问题建模为图上的优化问题来解决该问题。该问题属于广义的弧形路径问题,与非对称图上的农村邮差问题(RPP)密切相关。本文给出了一个整数线性规划公式,并证明了其正确性。利用最小代价流问题,我们开发了保证解质量的近似算法。这些保证也改进了非对称RPP的现有结果。主要算法根据所需图的结构将问题划分为三种情况,即由需要服务的特征诱导的图。我们在世界上50个人口最多的城市的道路网络上评估了我们的算法,这些城市由多达730个路段组成。该算法在改进启发式的基础上,在3秒内运行,并生成在最优值的10%以内的解决方案。我们在北卡罗来纳大学夏洛特校区的道路网络上用商用无人机实验证明了我们的算法。
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The single robot line coverage problem: Theory, algorithms, and experiments
Line coverage is the task of servicing a given set of one-dimensional features in an environment. It is important for the inspection of linear infrastructure such as road networks, power lines, and oil and gas pipelines. This paper addresses the single robot line coverage problem for aerial and ground robots by modeling it as an optimization problem on a graph. The problem belongs to the broad class of arc routing problems and is closely related to the rural postman problem (RPP) on asymmetric graphs. The paper presents an integer linear programming formulation with proofs of correctness. Using the minimum cost flow problem, we develop approximation algorithms with guarantees on the solution quality. These guarantees also improve the existing results for the asymmetric RPP. The main algorithm partitions the problem into three cases based on the structure of the required graph, that is, the graph induced by the features that require servicing. We evaluate our algorithms on road networks from the 50 most populous cities in the world, consisting of up to 730 road segments. The algorithms, augmented with improvement heuristics, run within 3 s and generate solutions that are within 10% of the optimum. We experimentally demonstrate our algorithms with commercial UAVs on the UNC Charlotte campus road network.
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来源期刊
Networks
Networks 工程技术-计算机:硬件
CiteScore
4.40
自引率
9.50%
发文量
46
审稿时长
12 months
期刊介绍: Network problems are pervasive in our modern technological society, as witnessed by our reliance on physical networks that provide power, communication, and transportation. As well, a number of processes can be modeled using logical networks, as in the scheduling of interdependent tasks, the dating of archaeological artifacts, or the compilation of subroutines comprising a large computer program. Networks provide a common framework for posing and studying problems that often have wider applicability than their originating context. The goal of this journal is to provide a central forum for the distribution of timely information about network problems, their design and mathematical analysis, as well as efficient algorithms for carrying out optimization on networks. The nonstandard modeling of diverse processes using networks and network concepts is also of interest. Consequently, the disciplines that are useful in studying networks are varied, including applied mathematics, operations research, computer science, discrete mathematics, and economics. Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally efficient network algorithms, and innovative case studies of successful network applications. We do not typically publish works that fall in the realm of pure graph theory (without significant algorithmic and modeling contributions) or papers that deal with engineering aspects of network design. Since the audience for this journal is then necessarily broad, articles that impact multiple application areas or that creatively use new or existing methodologies are especially appropriate. We seek to publish original, well-written research papers that make a substantive contribution to the knowledge base. In addition, tutorial and survey articles are welcomed. All manuscripts are carefully refereed.
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