Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model
المؤلفون المشاركون
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-19، 19ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-10-14
دولة النشر
مصر
عدد الصفحات
19
التخصصات الرئيسية
الملخص EN
HF-band radio-frequency identification (RFID) is a robust identification system that is rarely influenced by objects in the robot activity area or by illumination conditions.
An HF-band RFID system is capable of facilitating a reasonably accurate and robust self-localization of indoor mobile robots.
An RFID-based self-localization system for an indoor mobile robot requires prior knowledge of the map which contains the ID information and positions of the RFID tags used in the environment.
Generally, the map of RFID tags is manually built.
To reduce labor costs, the simultaneous localization and mapping (SLAM) technique is designed to localize the mobile robot and build a map of the RFID tags simultaneously.
In this study, multiple HF-band RFID readers are installed on the bottom of an omnidirectional mobile robot and RFID tags are spread on the floor.
Because the tag detection process of the HF-band RFID system does not follow a standard Gaussian distribution, extended Kalman filter- (EKF-) based landmark updates are unsuitable.
This paper proposes a novel SLAM method for the indoor mobile robot with a non-Gaussian detection model, by using the particle smoother for the landmark mapping and particle filter for the self-localization of the mobile robot.
The proposed SLAM method is evaluated through experiments with the HF-band RFID system which has the non-Gaussian detection model.
Furthermore, the proposed SLAM method is also evaluated by a range and bearing sensor which has the standard Gaussian detection model.
In particular, the proposed method is compared against two other SLAM methods: FastSLAM and SLAM methods utilize particle filter for both the landmark updating and robot self-localization.
The experimental results show the validity and superiority of the proposed SLAM method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Jun& Takahashi, Yasutake. 2019. Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model. Journal of Sensors،Vol. 2019, no. 2019, pp.1-19.
https://search.emarefa.net/detail/BIM-1187464
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Jun& Takahashi, Yasutake. Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model. Journal of Sensors No. 2019 (2019), pp.1-19.
https://search.emarefa.net/detail/BIM-1187464
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Jun& Takahashi, Yasutake. Particle Smoother-Based Landmark Mapping for the SLAM Method of an Indoor Mobile Robot with a Non-Gaussian Detection Model. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-19.
https://search.emarefa.net/detail/BIM-1187464
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1187464
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