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Approximation Algorithms for the UAV Path Planning with Object Coverage Constraints.

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Title: Approximation Algorithms for the UAV Path Planning with Object Coverage Constraints.
Authors: Wang, Jiawei1 (AUTHOR) 220211985@seu.edu.cn, Chau, Vincent1 (AUTHOR) vincentchau@seu.edu.cn, Wu, Weiwei1 (AUTHOR) weiweiwu@seu.edu.cn
Source: International Journal of Foundations of Computer Science. Jul2026, p1-25. 25p.
Subject Terms: *Mathematical optimization, *Mathematical programming, Approximation algorithms, Online algorithms, Video surveillance, Time complexity, Robotic path planning, Deterministic algorithms
Abstract: We study the problem of the Unmanned Aerial Vehicle (UAV) such that a specific set of objects needs to be observed while ensuring a quality of observation. Our goal is to determine the shortest path for the UAV. This paper proposes an offline algorithm with an approximation of (2 + 2n)(1 + 휖) where 휖 > 0 is a small constant, and n is the number of objects. We then propose several online algorithms in which objects are discovered during the process. To evaluate the performance of these algorithms, we conduct experimental comparisons. Our results show that the online algorithms perform similarly to the offline algorithm, but with significantly faster execution times ranging from 0.01 seconds to 200 seconds. We also show that our methods yield solutions with costs comparable to those obtained by the Gurobi optimizer that requires 30000 seconds of runtime. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Foundations of Computer Science is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
  Group: Ti
  Data: Approximation Algorithms for the UAV Path Planning with Object Coverage Constraints.
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  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Jiawei%22">Wang, Jiawei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 220211985@seu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chau%2C+Vincent%22">Chau, Vincent</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vincentchau@seu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Weiwei%22">Wu, Weiwei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> weiweiwu@seu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Foundations+of+Computer+Science%22">International Journal of Foundations of Computer Science</searchLink>. Jul2026, p1-25. 25p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+programming%22">Mathematical programming</searchLink><br /><searchLink fieldCode="DE" term="%22Approximation+algorithms%22">Approximation algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Online+algorithms%22">Online algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Video+surveillance%22">Video surveillance</searchLink><br /><searchLink fieldCode="DE" term="%22Time+complexity%22">Time complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Robotic+path+planning%22">Robotic path planning</searchLink><br /><searchLink fieldCode="DE" term="%22Deterministic+algorithms%22">Deterministic algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We study the problem of the Unmanned Aerial Vehicle (UAV) such that a specific set of objects needs to be observed while ensuring a quality of observation. Our goal is to determine the shortest path for the UAV. This paper proposes an offline algorithm with an approximation of (2 + 2n)(1 + 휖) where 휖 > 0 is a small constant, and n is the number of objects. We then propose several online algorithms in which objects are discovered during the process. To evaluate the performance of these algorithms, we conduct experimental comparisons. Our results show that the online algorithms perform similarly to the offline algorithm, but with significantly faster execution times ranging from 0.01 seconds to 200 seconds. We also show that our methods yield solutions with costs comparable to those obtained by the Gurobi optimizer that requires 30000 seconds of runtime. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Foundations of Computer Science is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1142/s0129054126430021
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 25
        StartPage: 1
    Subjects:
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Mathematical programming
        Type: general
      – SubjectFull: Approximation algorithms
        Type: general
      – SubjectFull: Online algorithms
        Type: general
      – SubjectFull: Video surveillance
        Type: general
      – SubjectFull: Time complexity
        Type: general
      – SubjectFull: Robotic path planning
        Type: general
      – SubjectFull: Deterministic algorithms
        Type: general
    Titles:
      – TitleFull: Approximation Algorithms for the UAV Path Planning with Object Coverage Constraints.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Wang, Jiawei
      – PersonEntity:
          Name:
            NameFull: Chau, Vincent
      – PersonEntity:
          Name:
            NameFull: Wu, Weiwei
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          Dates:
            – D: 16
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 01290541
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            – TitleFull: International Journal of Foundations of Computer Science
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