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A hybrid optimization algorithm combining A* and the dynamic window approach for automated guided vehicle control in static and dynamic environments.

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Title: A hybrid optimization algorithm combining A* and the dynamic window approach for automated guided vehicle control in static and dynamic environments.
Authors: Bhargava, Ankur1, ankurgsb21@gmail.com, Suhaib, Mohammad1,2, Singholi, Ajay K. S.1,2
Source: Robotica; Feb2026, Vol. 44 Issue 2, p408-470, 63p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 193632028
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A hybrid optimization algorithm combining A* and the dynamic window approach for automated guided vehicle control in static and dynamic environments.
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  Data: <searchLink fieldCode="AU" term="%22Bhargava%2C+Ankur%22">Bhargava, Ankur</searchLink><relatesTo>1</relatesTo>, <i>ankurgsb21@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Suhaib%2C+Mohammad%22">Suhaib, Mohammad</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AU" term="%22Singholi%2C+Ajay+K%2E+S%2E%22">Singholi, Ajay K. S.</searchLink><relatesTo>1,2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Robotica%22">Robotica</searchLink>; Feb2026, Vol. 44 Issue 2, p408-470, 63p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=193632028
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1017/S0263574725102944
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      – Code: eng
        Text: English
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        PageCount: 63
        StartPage: 408
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      – TitleFull: A hybrid optimization algorithm combining A* and the dynamic window approach for automated guided vehicle control in static and dynamic environments.
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            NameFull: Bhargava, Ankur
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            NameFull: Suhaib, Mohammad
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            NameFull: Singholi, Ajay K. S.
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 44
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