Show simple item record

dc.contributor.author Zim, Md Ziaul Haque
dc.contributor.author Sarkar, Md Sazzad
dc.contributor.author Nisi, Zeba Fauzia
dc.contributor.author Das, Nimai Chandra
dc.date.accessioned 2022-04-20T05:10:01Z
dc.date.available 2022-04-20T05:10:01Z
dc.date.issued 2021-04-09
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7920
dc.description.abstract Humans and animals have a brain and nervous system, and they process in-formation with neural networks. Trillions of neurons (nerve cells) exchanging brief electrical pulse called action potentials form neural networks. The endeavor of this paper aims to present the development of a neural network robot that mimics these biological structures to distinguish them from the squishy things in-side of animals. This robot is divided into hardware and OS (Operating System) part. In hardware, this robot has embedded systems that include an AVR microcontroller, L293D motor driver controller, OLED display, 4 LDR/Photoresist or, and DC gear motors. The AVR microcontroller working as the brain of this robot. This robot has an OS written in C programming language. This OS has a user interface that gives 3 options to select the operation mode. To train this robot a feed-forward back propagation network is used. Some results about testing and validating the robotic system are presented and discussed. en_US
dc.language.iso en_US en_US
dc.publisher IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), IEEE en_US
dc.subject Neural network en_US
dc.subject Photoresistor en_US
dc.subject Microcontroller en_US
dc.subject Machine learning en_US
dc.subject Supervised or Unsupervised learning en_US
dc.subject Robotics en_US
dc.title LFNNR en_US
dc.title.alternative Light Follower Neural Network Robot Conducted by Machine Learning Technique en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Browse

My Account

Statistics