An autonomous robot: Using ANN to navigate in a static path

Md Samiul Haque Sunny, Eklas Hossain, Taskia Nadriba Mimma, Shifat Hossain

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

A robot with autonomous navigation is not only able to find and follow its exact path but also able to avoid an obstacle which comes in its way without human assistance. This paper deals with an intelligent control of an autonomous robot which is trained with Artificial Neural Network to navigate in a partially structured environment which is full of static obstacles. The training capability according to the sensory input and its response to the obstacles are focused as two main challenges. In this work a Neural Network model is developed. This is done by algorithm of Artificial Intelligence. Then it is trained in Arduino platform for a navigation system designed for autonomous robot. To train the robot, a number of training samples are introduced. Ultrasonic sonar sensors are used with the Neural Network in order to find its route without colliding with any obstacle after the training. This novel approach in robot navigation is expected to open new doors of artificial intelligence in future.

Original languageEnglish
Title of host publication4th International Conference on Advances in Electrical Engineering, ICAEE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages291-296
Number of pages6
ISBN (Electronic)9781538608692
DOIs
StatePublished - 1 Jul 2017
Event4th International Conference on Advances in Electrical Engineering, ICAEE 2017 - Dhaka, Bangladesh
Duration: 28 Sep 201730 Sep 2017

Publication series

Name4th International Conference on Advances in Electrical Engineering, ICAEE 2017
Volume2018-January

Conference

Conference4th International Conference on Advances in Electrical Engineering, ICAEE 2017
Country/TerritoryBangladesh
CityDhaka
Period28/09/1730/09/17

Keywords

  • Arduino
  • Artificial Inteligance (AI)
  • Artificial Neural netowork (ANN)
  • Autonomous Navigation
  • Obstacle Avoidance

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