ID | 67593 |
フルテキストURL | |
著者 |
Toda, Yuichiro
Faculty of Environmental, Life, Natural Science and Technology, Okayama University
Masuyama, Naoki
Graduate School of Informatics, Osaka Metropolitan University
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抄録 | 3D space perception is one of the key technologies for autonomous mobile robots that perform tasks in unknown environments. Among these, building global topological maps for autonomous mobile robots is a challenging task. In this study, we propose a method for learning topological structures from unknown data distributions based on competitive learning, a type of unsupervised learning. For this purpose, adaptive resonance theory-based Topological Clustering (ATC), which can avoid catastrophic forgetting of previously measured point clouds, is applied as a learning method. Furthermore, by extending ATC with Different Topologies (ATC-DT) with multiple topological structures for extracting the traversable information of terrain environments, a path planning method is realized that can reach target points set in an unknown environment. Path planning experiments in unknown environments show that, compared to other methods, ATC-DT can build a global topology map with high accuracy and stability using only measured 3D point cloud and robot position information.
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キーワード | Adaptive resonance theory
autonomous mobile robot
topological map
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発行日 | 2024-08-12
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出版物タイトル |
IEEE Access
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巻 | 12巻
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出版者 | Institute of Electrical and Electronics Engineers
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開始ページ | 111371
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終了ページ | 111385
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ISSN | 2169-3536
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2024 The Authors.
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論文のバージョン | publisher
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DOI | |
Web of Science KeyUT | |
関連URL | isVersionOf https://doi.org/10.1109/ACCESS.2024.3442304
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ライセンス | https://creativecommons.org/licenses/by-nc-nd/4.0/
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Citation | Y. Toda and N. Masuyama, "Adaptive Resonance Theory-Based Global Topological Map Building for an Autonomous Mobile Robot," in IEEE Access, vol. 12, pp. 111371-111385, 2024, doi: 10.1109/ACCESS.2024.3442304.
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助成機関名 |
Japan Society for the Promotion of Science
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助成番号 | JP24K20870
JP22K12199
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