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Performance Evaluation of Various Path Planning Methods for Robotics and Computational Geometry | EAI Endorsed Transactions on Internet of Things

<!DOCTYPE html> <html lang="en-US" xml:lang="en-US"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title> Performance Evaluation of Various Path Planning Methods for Robotics and Computational Geometry | EAI Endorsed Transactions on Internet of Things </title> <link rel="icon" href="https://publications.eai.eu/public/journals/6/favicon_en_US.png"> <meta name="generator" content="Open Journal Systems 3.3.0.18"> <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/" /> <meta name="DC.Creator.PersonalName" content="Gokuldas Vedant Sarvesh Raikar"/> <meta name="DC.Creator.PersonalName" content="Gururaj HL"/> <meta name="DC.Creator.PersonalName" content="Vinayakumar Ravi"/> <meta name="DC.Creator.PersonalName" content="Wael Suliman"/> <meta name="DC.Date.created" scheme="ISO8601" content="2024-11-12"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2024-03-15"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2024-11-08"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2024-11-12"/> <meta name="DC.Description" xml:lang="en" content="INTRODUCTION: In integrating Spiral Coverage into Cellular Decomposition, which combines structured grid-based techniques with flexible, quick spiral traversal, time efficiency is increased.OBJECTIVES: In the field of robotics and computational geometry, the study proposes a comparative exploration of two prominent path planning methodologies—Boustrophedon Cellular Decomposition and the innovative Spiral Coverage. Boustrophedon coverage has limitations in time efficiency due to its back-and-forth motion pattern, which can lead to lengthier coverage periods, especially in congested areas. Nevertheless, it is useful in some situations. It is critical to address these time-related issues to make Boustrophedon algorithms more useful in practical settings. METHODS: The research centres on achieving comprehensive cell coverage, addressing the complexities arising from confined spaces and intricate geometries. While conventional methods emphasise route optimization between points, the coverage path planning approach seeks optimal paths that maximize coverage and minimize associated costs. This study delves into the theory, practical implementation, and application of Spiral Coverage integrated with established cellular decomposition techniques.RESULTS: Through comparative analysis, it illustrates the advantages of spiral coverage over boustrophedon coverage in diverse robotics and computational applications. The research highlights Spiral Coverage's superiority in terms of path optimization, computational efficiency, and adaptability, proposing a novel perspective into cell decomposition. The methodology integrates the Spiral Coverage concept, transcending traditional techniques reliant on grids or Voronoi diagrams. Rigorous evaluation validates its potential to enhance path planning, exemplifying a substantial advancement in robotics and computational geometry.CONCLUSION: Our findings show that spiral coverage is on an average 45% more efficient than conventional Boustrophedon coverage. This paper set the basis for the future work on how different algorithms can traverse different shapes more efficiently."/> <meta name="DC.Format" scheme="IMT" content="application/pdf"/> <meta name="DC.Identifier" content="5433"/> <meta name="DC.Identifier.DOI" content="10.4108/eetiot.5433"/> <meta name="DC.Identifier.URI" content="https://publications.eai.eu/index.php/IoT/article/view/5433"/> <meta name="DC.Language" scheme="ISO639-1" content="en"/> <meta name="DC.Rights" content="Copyright (c) 2024 EAI Endorsed Transactions on Internet of Things"/> <meta name="DC.Rights" content="https://creativecommons.org/licenses/by/3.0/"/> <meta name="DC.Source" content="EAI Endorsed Transactions on Internet of Things"/> <meta name="DC.Source.ISSN" content="2414-1399"/> <meta name="DC.Source.Volume" content="11"/> <meta name="DC.Source.URI" content="https://publications.eai.eu/index.php/IoT"/> <meta name="DC.Subject" xml:lang="en" content="Coverage Path Planning"/> <meta name="DC.Title" content="Performance Evaluation of Various Path Planning Methods for Robotics and Computational Geometry"/> <meta name="DC.Type" content="Text.Serial.Journal"/> <meta name="DC.Type.articleType" content="Research article"/> <meta name="gs_meta_revision" content="1.1"/> <meta name="citation_journal_title" content="EAI Endorsed Transactions on Internet of Things"/> <meta name="citation_journal_abbrev" content="EAI Endorsed Trans IoT"/> <meta name="citation_issn" content="2414-1399"/> <meta name="citation_author" content="Gokuldas Vedant Sarvesh Raikar"/> <meta name="citation_author_institution" content="Manipal Institute of Technology Bengaluru"/> <meta name="citation_author" content="Gururaj HL"/> <meta name="citation_author_institution" content="Manipal Institute of Technology"/> <meta name="citation_author" content="Vinayakumar Ravi"/> <meta name="citation_author_institution" content="Prince Mohammad bin Fahd University"/> <meta name="citation_author" content="Wael Suliman"/> <meta name="citation_author_institution" content="Prince Mohammad bin Fahd University"/> <meta name="citation_title" content="Performance Evaluation of Various Path Planning Methods for Robotics and Computational Geometry"/> <meta name="citation_language" content="en"/> <meta name="citation_date" content="2025"/> <meta name="citation_volume" content="11"/> <meta name="citation_doi" content="10.4108/eetiot.5433"/> <meta name="citation_abstract_html_url" content="https://publications.eai.eu/index.php/IoT/article/view/5433"/> <meta name="citation_keywords" xml:lang="en" content="Path planning"/> <meta name="citation_keywords" xml:lang="en" content="Computational geometry"/> <meta name="citation_keywords" xml:lang="en" content="Boustrophedon Cellular Decomposition"/> <meta name="citation_keywords" xml:lang="en" content="Spiral Coverage"/> <meta name="citation_keywords" xml:lang="en" content="Coverage Path Planning"/> <meta name="citation_pdf_url" content="https://publications.eai.eu/index.php/IoT/article/download/5433/3450"/> <meta name="citation_reference" content="[1] De Carvalho RN, Vidal HA, Vieira P, Ribeiro MI. 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Annual Reviews in Control. 2022 Jan 1;53:391-404."/> <meta name="og:site_name" content="EAI Endorsed Transactions on Internet of Things"/> <meta name="og:type" content="article"/> <meta name="og:title" content="Performance Evaluation of Various Path Planning Methods for Robotics and Computational Geometry"/> <meta name="og:description" content="INTRODUCTION: In integrating Spiral Coverage into Cellular Decomposition, which combines structured grid-based techniques with flexible, quick spiral traversal, time efficiency is increased. OBJECTIVES: In the field of robotics and computational geometry, the study proposes a comparative exploration of two prominent path planning methodologies—Boustrophedon Cellular Decomposition and the innovative Spiral Coverage. Boustrophedon coverage has limitations in time efficiency due to its back-and-forth motion pattern, which can lead to lengthier coverage periods, especially in congested areas. Nevertheless, it is useful in some situations. It is critical to address these time-related issues to make Boustrophedon algorithms more useful in practical settings. METHODS: The research centres on achieving comprehensive cell coverage, addressing the complexities arising from confined spaces and intricate geometries. While conventional methods emphasise route optimization between points, the coverage path planning approach seeks optimal paths that maximize coverage and minimize associated costs. This study delves into the theory, practical implementation, and application of Spiral Coverage integrated with established cellular decomposition techniques. RESULTS: Through comparative analysis, it illustrates the advantages of spiral coverage over boustrophedon coverage in diverse robotics and computational applications. The research highlights Spiral Coverage's superiority in terms of path optimization, computational efficiency, and adaptability, proposing a novel perspective into cell decomposition. The methodology integrates the Spiral Coverage concept, transcending traditional techniques reliant on grids or Voronoi diagrams. Rigorous evaluation validates its potential to enhance path planning, exemplifying a substantial advancement in robotics and computational geometry. CONCLUSION: Our findings show that spiral coverage is on an average 45% more efficient than conventional Boustrophedon coverage. This paper set the basis for the future work on how different algorithms can traverse different shapes more efficiently. 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</span> <span class="affiliation"> Manipal Institute of Technology Bengaluru </span> </li> <li> <span class="name"> Gururaj HL </span> <span class="affiliation"> Manipal Institute of Technology </span> </li> <li> <span class="name"> Vinayakumar Ravi </span> <span class="affiliation"> Prince Mohammad bin Fahd University <a href="https://ror.org/03d64na34"><?xml version="1.0" encoding="UTF-8" standalone="no"?> <!-- Generator: Adobe Illustrator 23.0.1, SVG Export Plug-In . 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-2.31,0.69 -3.65,0.77 -1.35,0.09 -2.62,0.13 -3.83,0.13 h -7.91 V 39.89 h 8.77 c 1.2,0 2.44,0.09 3.7,0.26 1.26,0.17 2.38,0.5 3.35,0.99 0.97,0.49 1.78,1.19 2.41,2.11 0.63,0.92 0.95,2.15 0.95,3.7 0,1.65 -0.36,2.94 -1.08,3.86 z" id="path80" inkscape:connector-curvature="0" style="fill:#202826" /> </g> </g> </switch> </svg> </a> </span> </li> </ul> </section> <section class="item doi"> <h2 class="label"> DOI: </h2> <span class="value"> <a href="https://doi.org/10.4108/eetiot.5433"> https://doi.org/10.4108/eetiot.5433 </a> </span> </section> <section class="item keywords"> <h2 class="label"> Keywords: </h2> <span class="value"> Path planning, Computational geometry, Boustrophedon Cellular Decomposition, Spiral Coverage, Coverage Path Planning </span> </section> <section class="item abstract"> <h2 class="label">Abstract</h2> <p>INTRODUCTION: In integrating Spiral Coverage into Cellular Decomposition, which combines structured grid-based techniques with flexible, quick spiral traversal, time efficiency is increased.</p><p>OBJECTIVES: In the field of robotics and computational geometry, the study proposes a comparative exploration of two prominent path planning methodologies—Boustrophedon Cellular Decomposition and the innovative Spiral Coverage. Boustrophedon coverage has limitations in time efficiency due to its back-and-forth motion pattern, which can lead to lengthier coverage periods, especially in congested areas. Nevertheless, it is useful in some situations. It is critical to address these time-related issues to make Boustrophedon algorithms more useful in practical settings. </p><p>METHODS: The research centres on achieving comprehensive cell coverage, addressing the complexities arising from confined spaces and intricate geometries. While conventional methods emphasise route optimization between points, the coverage path planning approach seeks optimal paths that maximize coverage and minimize associated costs. This study delves into the theory, practical implementation, and application of Spiral Coverage integrated with established cellular decomposition techniques.</p><p>RESULTS: Through comparative analysis, it illustrates the advantages of spiral coverage over boustrophedon coverage in diverse robotics and computational applications. The research highlights Spiral Coverage's superiority in terms of path optimization, computational efficiency, and adaptability, proposing a novel perspective into cell decomposition. The methodology integrates the Spiral Coverage concept, transcending traditional techniques reliant on grids or Voronoi diagrams. Rigorous evaluation validates its potential to enhance path planning, exemplifying a substantial advancement in robotics and computational geometry.</p><p>CONCLUSION: Our findings show that spiral coverage is on an average 45% more efficient than conventional Boustrophedon coverage. This paper set the basis for the future work on how different algorithms can traverse different shapes more efficiently.</p> </section> <div class="item downloads_chart"> <h3 class="label"> Downloads </h3> <div class="value"> <canvas class="usageStatsGraph" data-object-type="Submission" data-object-id="5433"></canvas> <div class="usageStatsUnavailable" data-object-type="Submission" data-object-id="5433"> Download data is not yet available. </div> </div> </div> &lt;br data-mce-bogus="1"&gt; <!-- Plum Analytics --> <a href="https://plu.mx/plum/a/?doi=10.4108/eetiot.5433" class="plumx-summary" data-hide-when-empty="true" data-orientation="horizontal" ></a> <!-- /Plum Analytics --> &lt;br data-mce-bogus="1"&gt; <section class="item references"> <h2 class="label"> References </h2> <div class="value"> <p>[1] De Carvalho RN, Vidal HA, Vieira P, Ribeiro MI. Complete coverage path planning and guidance for cleaning robots. 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