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Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter
المؤلفون المشاركون
Han, Yu
Liu, Peng
Xiao, Yao
Lu, Peng
Cai, Chengtao
Zhu, Qidan
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-01-29
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
This paper proposes a novel motion planning method for an autonomous ground mobile robot to address dynamic surroundings, nonlinear program, and robust optimization problems.
A planner based on the recurrent fuzzy neural network (RFNN) is designed to program trajectory and motion of mobile robots to reach target.
And, obstacle avoidance is achieved.
In RFNN, inference capability of fuzzy logic and learning capability of neural network are combined to improve nonlinear programming performance.
A recurrent frame with self-feedback loops in RFNN enhances stability and robustness of the structure.
The extended Kalman filter (EKF) is designed to train weights of RFNN considering the kinematic constraint of autonomous mobile robots as well as target and obstacle constraints.
EKF’s characteristics of fast convergence and little limit in training data make it suitable to train the weights in real time.
Convergence of the training process is also analyzed in this paper.
Optimization technique and update strategy are designed to improve the robust optimization of a system in dynamic surroundings.
Simulation experiment and hardware experiment are implemented to prove the effectiveness of the proposed method.
Hardware experiment is carried out on a tracked mobile robot.
An omnidirectional vision is used to locate the robot in the surroundings.
Forecast improvement of the proposed method is then discussed at the end.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhu, Qidan& Han, Yu& Liu, Peng& Xiao, Yao& Lu, Peng& Cai, Chengtao. 2019. Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129356
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhu, Qidan…[et al.]. Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1129356
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhu, Qidan& Han, Yu& Liu, Peng& Xiao, Yao& Lu, Peng& Cai, Chengtao. Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129356
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1129356
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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