Path Planning for Sensor Data Collection by Using UAVs

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publication14th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2018
PublisherIEEE
Pages199-205
ISBN (Electronic)9781728105482
ISBN (Print)9781728105499
Publication statusPublished - Dec 2018

Publication series

NameProceedings - International Conference on Mobile Ad-Hoc and Sensor Networks, MSN
PublisherIEEE

Conference

Title14th International Conference on Mobile Ad-hoc and Sensor Networks (MSN 2018)
PlaceChina
CityShenyang
Period6 - 8 December 2018

Abstract

In sparse wireless sensor networks, a UAV is used to collect the sensing data. Each sensor node has a limited transmission range and the UAV has to traverse the transmission range of all sensor nodes to collect data without exhausting energy of the UAV. To minimize the total energy consumption of the UAV on the flying and collecting data, it is essential to consider the tradeoff between path length and data collection time when planning path. In this paper, we show that the optimization problem can be regarded as the traveling salesman problem with neighborhood, which is known to be NP-hard. To address the problem, we decompose it into two subproblems, 1) weighted set cover problem; and 2) a combined optimization problem. Then we solve the first one by a greedy algorithm and the second by an improved shuffled frog-leaping algorithm. We also simulate the proposed algorithm to evaluate its performance.

Research Area(s)

  • UAV, data collection, path planning, energy efficient

Citation Format(s)

Path Planning for Sensor Data Collection by Using UAVs. / Kong, Baichuan; Huang, Hejiao; Jia, Xiaohua.

14th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2018. IEEE, 2018. p. 199-205 8691979 (Proceedings - International Conference on Mobile Ad-Hoc and Sensor Networks, MSN).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review