An Improved Deep Residual Network-Based Semantic Simultaneous Localization and Mapping Method for Monocular Vision Robot
المؤلفون المشاركون
Gong, Tao
Gu, Yafei
Zhu, Jinxiu
Fan, Xinnan
Ni, Jianjun
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-10
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
The robot simultaneous localization and mapping (SLAM) is a very important and useful technology in the robotic field.
However, the environmental map constructed by the traditional visual SLAM method contains little semantic information, which cannot satisfy the needs of complex applications.
The semantic map can deal with this problem efficiently, which has become a research hot spot.
This paper proposed an improved deep residual network- (ResNet-) based semantic SLAM method for monocular vision robots.
In the proposed approach, an improved image matching algorithm based on feature points is presented, to enhance the anti-interference ability of the algorithm.
Then, the robust feature point extraction method is adopted in the front-end module of the SLAM system, which can effectively reduce the probability of camera tracking loss.
In addition, the improved key frame insertion method is introduced in the visual SLAM system to enhance the stability of the system during the turning and moving of the robot.
Furthermore, an improved ResNet model is proposed to extract the semantic information of the environment to complete the construction of the semantic map of the environment.
Finally, various experiments are conducted and the results show that the proposed method is effective.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ni, Jianjun& Gong, Tao& Gu, Yafei& Zhu, Jinxiu& Fan, Xinnan. 2020. An Improved Deep Residual Network-Based Semantic Simultaneous Localization and Mapping Method for Monocular Vision Robot. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1138813
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ni, Jianjun…[et al.]. An Improved Deep Residual Network-Based Semantic Simultaneous Localization and Mapping Method for Monocular Vision Robot. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1138813
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ni, Jianjun& Gong, Tao& Gu, Yafei& Zhu, Jinxiu& Fan, Xinnan. An Improved Deep Residual Network-Based Semantic Simultaneous Localization and Mapping Method for Monocular Vision Robot. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1138813
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138813
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر