A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique

Navigation strategy to control the motion of robots is essential to develop a stable system in swarm robotics. Swarm robotics is a group of homogenous robot working together to achieve a target. This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. BA as a...

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Main Authors:	Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa
Format:	Conference or Workshop Item
Language:	English
Published:	2018
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/22484/ http://umpir.ump.edu.my/id/eprint/22484/1/A%20Navigation%20Strategy%20for%20Swarm%20Robotics%20Based%20on%20Bat1.pdf

id	ump-22484
recordtype	eprints
spelling	ump-224842018-10-29T03:49:30Z http://umpir.ump.edu.my/id/eprint/22484/ A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Bayuaji, Luhur Muhammad, Syafrullah Zulkifli, Musa TK Electrical engineering. Electronics Nuclear engineering Navigation strategy to control the motion of robots is essential to develop a stable system in swarm robotics. Swarm robotics is a group of homogenous robot working together to achieve a target. This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. BA as a nature inspired algorithm is used in the system to determine current location and search for future position of each robots inspired by echolocation behavior of microbats. Five robots which represent five particles in this study need to move from designated initial positions to one point of desired position. All the robots need to meet at the point to verify the success of the navigation strategy. Number of iterations and accuracy of localization are presented and compared with navigation strategy based on Particle Swarm Optimization (PSO). The analysis of the performance of proposed algorithm is conducted by considering two different parameters. First is the number of iterations to achieve the desired position. Second is the accuracy which is the difference between the final position of the swarm robot and the desired position. The result shows that the number of iteration for BA technique and PSO technique are 42 and 77 respectively. In term of accuracy, BA has 0.0039% of error while PSO 0.0079% error. It is shown that BA outperformed PSO technique with less number of iterations and higher accuracy. 2018 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22484/1/A%20Navigation%20Strategy%20for%20Swarm%20Robotics%20Based%20on%20Bat1.pdf Nur Aisyah Syafinaz, Suarin and Pebrianti, Dwi and Bayuaji, Luhur and Muhammad, Syafrullah and Zulkifli, Musa (2018) A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique. In: Symposium on Instrumentation and Sensing Technology (SoINSET 2018), 5 August 2018 , Tunku Tun Aminah Library, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat, Malaysia. pp. 1-8..
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Bayuaji, Luhur Muhammad, Syafrullah Zulkifli, Musa A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
description	Navigation strategy to control the motion of robots is essential to develop a stable system in swarm robotics. Swarm robotics is a group of homogenous robot working together to achieve a target. This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. BA as a nature inspired algorithm is used in the system to determine current location and search for future position of each robots inspired by echolocation behavior of microbats. Five robots which represent five particles in this study need to move from designated initial positions to one point of desired position. All the robots need to meet at the point to verify the success of the navigation strategy. Number of iterations and accuracy of localization are presented and compared with navigation strategy based on Particle Swarm Optimization (PSO). The analysis of the performance of proposed algorithm is conducted by considering two different parameters. First is the number of iterations to achieve the desired position. Second is the accuracy which is the difference between the final position of the swarm robot and the desired position. The result shows that the number of iteration for BA technique and PSO technique are 42 and 77 respectively. In term of accuracy, BA has 0.0039% of error while PSO 0.0079% error. It is shown that BA outperformed PSO technique with less number of iterations and higher accuracy.
format	Conference or Workshop Item
author	Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Bayuaji, Luhur Muhammad, Syafrullah Zulkifli, Musa
author_facet	Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Bayuaji, Luhur Muhammad, Syafrullah Zulkifli, Musa
author_sort	Nur Aisyah Syafinaz, Suarin
title	A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
title_short	A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
title_full	A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
title_fullStr	A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
title_full_unstemmed	A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique
title_sort	navigation strategy for swarm robotics based on bat algorithm optimization technique
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/22484/ http://umpir.ump.edu.my/id/eprint/22484/1/A%20Navigation%20Strategy%20for%20Swarm%20Robotics%20Based%20on%20Bat1.pdf
first_indexed	2023-09-18T22:33:29Z
last_indexed	2023-09-18T22:33:29Z
_version_	1777416441574719488

A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique

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