Simulating the immune inspired energy charging mechanism for swarm robotic systems
Fault tolerance or the property that enables a system to continue its operation properly in the event of partial failure is one of the most desired criteria in swarm robotic systems. There is a possibility that a continuous failure of the member(s) of the swarm, will reflect on the overall perform...
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Asian Research Publishing Network
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iium-593662018-01-03T03:05:00Z http://irep.iium.edu.my/59366/ Simulating the immune inspired energy charging mechanism for swarm robotic systems Al Haek, Mohammed Ismail, Amelia Ritahani QA75 Electronic computers. Computer science Fault tolerance or the property that enables a system to continue its operation properly in the event of partial failure is one of the most desired criteria in swarm robotic systems. There is a possibility that a continuous failure of the member(s) of the swarm, will reflect on the overall performance of the systems. In this paper, we proposed an immune-inspired energy charging mechanism, which is inspired by the process of immune responses. The proposed energy charging mechanism is presented, simulated and compared with another common energy charging mechanism, which is the use of contact-less energy charging area. Based on the experimental results, the proposed mechanism shows an improvement in terms of performance time and aggregate energy of the swarm to perform its task. Asian Research Publishing Network 2017-10-31 Article PeerReviewed application/pdf en http://irep.iium.edu.my/59366/1/SIMULATING%20THE%20IMMUNE%20INSPIRED%20ENERGY.pdf application/pdf en http://irep.iium.edu.my/59366/7/59366_Simulating%20the%20immune%20inspired%20energy_scopus.pdf Al Haek, Mohammed and Ismail, Amelia Ritahani (2017) Simulating the immune inspired energy charging mechanism for swarm robotic systems. Journal of Theoretical and Applied Information Technology, 95 (20). pp. 5473-5483. ISSN 1992-8645 E-ISSN 1817-3195 http://www.jatit.org/volumes/ninetyfive20.php |
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QA75 Electronic computers. Computer science |
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QA75 Electronic computers. Computer science Al Haek, Mohammed Ismail, Amelia Ritahani Simulating the immune inspired energy charging mechanism for swarm robotic systems |
description |
Fault tolerance or the property that enables a system to continue its operation properly in the event of partial
failure is one of the most desired criteria in swarm robotic systems. There is a possibility that a continuous
failure of the member(s) of the swarm, will reflect on the overall performance of the systems. In this paper,
we proposed an immune-inspired energy charging mechanism, which is inspired by the process of immune
responses. The proposed energy charging mechanism is presented, simulated and compared with another
common energy charging mechanism, which is the use of contact-less energy charging area. Based on the
experimental results, the proposed mechanism shows an improvement in terms of performance time and
aggregate energy of the swarm to perform its task. |
format |
Article |
author |
Al Haek, Mohammed Ismail, Amelia Ritahani |
author_facet |
Al Haek, Mohammed Ismail, Amelia Ritahani |
author_sort |
Al Haek, Mohammed |
title |
Simulating the immune inspired energy charging mechanism for swarm robotic systems |
title_short |
Simulating the immune inspired energy charging mechanism for swarm robotic systems |
title_full |
Simulating the immune inspired energy charging mechanism for swarm robotic systems |
title_fullStr |
Simulating the immune inspired energy charging mechanism for swarm robotic systems |
title_full_unstemmed |
Simulating the immune inspired energy charging mechanism for swarm robotic systems |
title_sort |
simulating the immune inspired energy charging mechanism for swarm robotic systems |
publisher |
Asian Research Publishing Network |
publishDate |
2017 |
url |
http://irep.iium.edu.my/59366/ http://irep.iium.edu.my/59366/ http://irep.iium.edu.my/59366/1/SIMULATING%20THE%20IMMUNE%20INSPIRED%20ENERGY.pdf http://irep.iium.edu.my/59366/7/59366_Simulating%20the%20immune%20inspired%20energy_scopus.pdf |
first_indexed |
2023-09-18T21:24:07Z |
last_indexed |
2023-09-18T21:24:07Z |
_version_ |
1777412076940034048 |