EconPapers    
Economics at your fingertips  
 

Artificial Intelligence (AI)-Powered Line Follower Robot with Hurdle Detection and Voice Control

Rana Qamar Hayat, Fida Hussain and Umer Masood
Additional contact information
Rana Qamar Hayat: Research Scholar, Faculty of Computing, University of Okara, Pakistan
Fida Hussain: Research Scholar, Faculty of Computing, University of Okara, Pakistan
Umer Masood: Artificial Intelligence (AI)-Powered Line Follower Robot with Hurdle Detection and Voice Control

International Journal of Latest Technology in Engineering, Management & Applied Science, 2024, vol. 13, issue 11, 79-83

Abstract: In this paper, we propose a voice controlled line following robot with the ability to trace the set path and avoid hurdles while moving autonomously. Line-following robots have been around for decades, but this setup uses AI algorithms and fresnel lenses to improve accuracy More Traditional line-following robots often face drawbacks in dealing with intricate environments, but those are addressed here via user control over voice recognition, as-well-as obstacle detection through ultrasonic sensors. The robot is controlled over an Arduino UNO microcontroller and the (advance) features that it offers allows the robot to operate independently with lesser human interactions, the applications of such a robot will span across Transportation & logistics, Industrial Automation and Personal Assistance. This study reveals the potential of this robot to improve precision and flexibility in a realistic usage condition, thereby providing an important tool for automation with safety and productivity.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.13Issue11/79-83.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-13-issue-11/79-83.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:13:y:2024:i:11:p:79-83

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().

 
Page updated 2025-03-19
Handle: RePEc:bjb:journl:v:13:y:2024:i:11:p:79-83