Model of Environment Representation Architecture for Intelligent Robot
using Artificial Neural Network
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This book presents a model of Environment Representation Architecture for Intelligent Robot using artificial Neural Network. The model consists of a vehicle, an environment and landmarks. The proposed method is based on using Simultaneous Localization and Mapping based on Artificial Neural Network, back propagation algorithm, to be trained on predefined datasets on some environment. The Finding in this book dun Using Artificial Neural on the Simultaneous Localization and Mapping enhances the obtained maps of the robot. Limitation of this book to test the proposed system, different maps with di...
This book presents a model of Environment Representation Architecture for Intelligent Robot using artificial Neural Network. The model consists of a vehicle, an environment and landmarks. The proposed method is based on using Simultaneous Localization and Mapping based on Artificial Neural Network, back propagation algorithm, to be trained on predefined datasets on some environment. The Finding in this book dun Using Artificial Neural on the Simultaneous Localization and Mapping enhances the obtained maps of the robot. Limitation of this book to test the proposed system, different maps with different datasets are required, however, these datasets, need expensive sensors, vehicles and GPS receivers to be built. The Originality he contribution of this work, is the use of Artificial Neural Network Back Propagation algorithm on the Simultaneous Localization and Mapping algorithm to obtain enhanced results, enhanced maps and datasets obtained by the robot Using several methods of preparing data sets for the landmarks of an environment, SLAM was able to navigate and build its own map of landmarks based on them.
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