Autonomous Robot Navigation Based On Recurrent Neural Networks

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

The main objective of this research is to present a reactive navigation algorithm for wheeled mobile robots under non-holonomic constraints and in unknown environments. Two techniques are proposed: a geometrical based technique and a neural network based technique. The mobile robot travels to a pre-defined goal position safely and efficiently without any prior map of the environment by modulating its steering angle and turning radius. The dimensions and shape of the robot are incorporated to determine the set of all possible collision-free steering angles. The algorithm then selects the best steering angle candidate. In the geometrical navigation technique, a safe turning radius is computed based on an equation derived from the geometry of the problem. On the other hand, the neural-based technique aims to generate an optimized trajectory by using a user-defined objective function which minimizes the traveled distance to the goal position while avoiding obstacles. A mobile robot is developed to test the performances of the two algorithms. The results demonstrate that the algorithms are capable of driving the robot safely across a variety of indoor environments.

روابط وملفات

التعريف والنوع

رقم الوثيقة

f9d89722-4f3f-4c60-84a9-de3b5b9b5eb4

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

45944_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Mariam Qusai Al-Sagban","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"Rached Dhaouadi","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

English

المصدر والدورية

اسم المصدر

Autonomous Robot Navigation Based On Recurrent Neural Networks

المحتوى والصفحات

عدد الصفحات

0

إشراف وإعداد

الإشراف

Rached Dhaouadi

الإعداد

Mariam Qusai Al-Sagban

الاقتباسات الببليوغرافية