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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JERA</journal-id><journal-title-group><journal-title>Journal of Electronic Research and Application</journal-title></journal-title-group><issn>2208-3502</issn><eissn>2208-3510</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jera.v9i5.12397</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>The Design and Implementation of an Intelligent Guide Dog Robot Based on Multimodal Perception</title><url>https://artdesignp.com/journal/JERA/9/5/10.26689/jera.v9i5.12397</url><author>ZhuYanxuan</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>5</issue><history><date date-type="pub"><published-time>2025-10-21</published-time></date></history><abstract>Aiming at the problems of traditional guide devices such as single environmental perception and poor terrain adaptability, this paper proposes an intelligent guide system based on a quadruped robot platform. Data fusion between millimeter-wave radar (with an accuracy of ± 0.1°) and an RGB-D camera is achieved through multi-sensor spatiotemporal registration technology, and a dataset suitable for guide dog robots is constructed. For the application scenario of edge-end guide dog robots, a lightweight CA-YOLOv11 target detection model integrated with an attention mechanism is innovatively adopted, achieving a comprehensive recognition accuracy of 95.8% in complex scenarios, which is 2.2% higher than that of the benchmark YOLOv11 network. The system supports navigation on complex terrains such as stairs (25 cm steps) and slopes (35° gradient), and the response time to sudden disturbances is shortened to 100 ms. Actual tests show that the navigation success rate reaches 95% in eight types of scenarios, the user satisfaction score is 4.8/5.0, and the cost is 50% lower than that of traditional guide dogs.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Hutter M, Gehring C, Lauber A, et al., 2016, Anymal — A Highly Mobile and Dynamic Quadrupedal Robot, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea (South), 38–44.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Ultralytics, 2020, YOLOv5: A Family of Object Detection Architectures and Models. 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