DEVELOPMENT OF LEADER AND FOLLOWER STRATEGY FOR SWARM ROBOT APPLICATIONS

Authors

  • Humairah Mansor School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia
  • Abdul Hamid Adom School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia
  • Norasmadi Abdul Rahim School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia

DOI:

https://doi.org/10.11113/jt.v77.6791

Keywords:

Communication, leader-follower, RSSI, swarm, wireless, X-Bee

Abstract

Swarming robots basically consist of a group of several simple robots that interact and collaborate with each other to achieve shared goals. A single robot system is not suitable to be used as an agent for the navigation usually covers a wide range of area. Therefore, a group of simple robots is introduced. A group of robots can perform their tasks together in a more efficient way compared to a single robot; hence develop a more robust system. In order to interact, a wireless communication strategy is implemented to enable the group of mobile robots to perform their tasks. This project implements the swarming algorithm by supplementing the ability of mobile robot platforms with autonomy and odour detection. The work focused on the localization of chemical odour source in the testing environment and the leader and follower swarm formation through wireless communication. To enable the mobile robots to communicate with each other and able to perform leader and follower designation once the target has been found, the RSSI value of X-Bee module is used.

References

Beni, G. 2005. From Swarm Intelligence to Swarm Robotics. Swarm Robotics WS 2004. Berlin: Springer-Verlag.

Parker, L. E. 2003. Current Research in Multirobot Systems. Artificial Life and Robotics. 7(1-2): 1-5.

Marjovi, A., Nunes, J., Sousa, P., Faria R., and Marques, L. 2010. An Olfactory Based Robot Swarm Navigation Method. IEEE International Conference on Robotics and Automation Anchorage. Alaska, USA.

Noh, S. A., Lee, W. J. and Ye, J. Y. 2008. Comparison of the Mechanisms of the Zigbee’s Indoor Localization Algorithm. 9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing.

Mohan, Y. and Ponnambalam, S. G. 2009. An Extensive Review of Research in Swarm Robotics. World Congress on Nature & Biologically Inspired Computing (NaBIC). Kuala Lumpur, Malaysia.

Arvin, F., Doraisamy, S., Samsudin, K. and Ramli, A. R. 2010. Self-Localization of Swarm Robots Based on Voice Signal Acquisition. International Conference on Computer and Communication Engineering (ICCCE 2010). Kuala Lumpur, Malaysia.

Nasser, M. I. 2008. On E-Puck Mobile Robots for Distributed Robotics. Bachelor’s Dissertation, National University of Singapore. Singapore.

Quasiben. 2009. Proximity Sensing Pocket Squares. [Online]. From: http://www.instructables.com/id/Proximity-Sensing-Pocket-Squares/step2/RSSI-Discussions/. [Accessed on March 20, 2014].

Downloads

Published

2015-12-16

Issue

Section

Science and Engineering

How to Cite

DEVELOPMENT OF LEADER AND FOLLOWER STRATEGY FOR SWARM ROBOT APPLICATIONS. (2015). Jurnal Teknologi, 77(28). https://doi.org/10.11113/jt.v77.6791