Development of Robotic Platform for Swarm Robots in Fire Detection Application

Authors

  • Sarun Chattunyakit School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12000, Thailand
  • Toshiaki Kondo School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12000, Thailand
  • Itthisek Nilkhamhang School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12000, Thailand

Keywords:

swarm robotic platform, fire detection, leader-follower, swarm intelligence

Abstract

In recent years, a team of simple robots, so-called swarm robots, can perform the same level of difficult tasks as a more complicated robot. Due to their abilities, they can be applied to many situations. Fire detection is one application that can be combined with swarm intelligence to increase efficiency and effectiveness. This paper presents a new swarm robotic platform for a fire detection task called FiFiBot that has been developed for low cost and high performance. The average cost per FiFiBot is USD 140. Compared with conventional designs, they are better in terms of computational speed, cost and the number of included sensors. Moreover, two FiFiBots were programmed to perform a leader-follower routine with fire detection, and were successfully tested. Hence, FiFiBots are feasible robotic platforms to be used for research and educational purposes for swarm systems.

Downloads

Published

2013-12-31

How to Cite

Chattunyakit, Sarun, Toshiaki Kondo, and Itthisek Nilkhamhang. 2013. “Development of Robotic Platform for Swarm Robots in Fire Detection Application”. Agriculture and Natural Resources 47 (6). Bangkok, Thailand:967-76. https://li01.tci-thaijo.org/index.php/anres/article/view/243165.

Issue

Vol. 47 No. 6 (2013): November-December

Section

Research Article

License

online 2452-316X print 2468-1458/Copyright © 2022. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/),
production and hosting by Kasetsart University of Research and Development Institute on behalf of Kasetsart University.