An artificial immune system for self-healing in swarm robotic systems

Amelia R. Ismail; Jan D. Bjerknes; Jon Timmis; Alan Winfield

doi:10.1007/978-3-319-23108-2_6

An artificial immune system for self-healing in swarm robotic systems

Amelia R. Ismail, Jan D. Bjerknes, Jon Timmis^*, Alan Winfield

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we propose an approach to self-healing swarm robotic systems and take inspiration from the process of granuloma formation, a process of containment and repair found in the immune system. We use a case study of a swarm performing team work where previous works have demonstrated that partially failed robots have the most detrimental effect on overall swarm behaviour. In response this, we have developed an immune inspired approach that permits the recovery from certain failure modes during operation of the swarm, overcoming issues that effect swarm behaviour associated with partially failed robots.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer
Pages	61-74
Number of pages	14
Volume	9303
ISBN (Print)	9783319231075
DOIs	https://doi.org/10.1007/978-3-319-23108-2_6
Publication status	Published - 1 Jan 2015
Event	10th International Conference on Information Processing in Cells and Tissues, IPCAT 2015 - San Diego, United Kingdom Duration: 14 Sept 2015 → 16 Sept 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9303
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	10th International Conference on Information Processing in Cells and Tissues, IPCAT 2015
Country/Territory	United Kingdom
City	San Diego
Period	14/09/15 → 16/09/15

Access to Document

10.1007/978-3-319-23108-2_6

Cite this

Ismail, A. R., Bjerknes, J. D., Timmis, J., & Winfield, A. (2015). An artificial immune system for self-healing in swarm robotic systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9303, pp. 61-74). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9303). Springer. https://doi.org/10.1007/978-3-319-23108-2_6

Ismail, Amelia R. ; Bjerknes, Jan D. ; Timmis, Jon et al. / An artificial immune system for self-healing in swarm robotic systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9303 Springer, 2015. pp. 61-74 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ffdd76b28b8143a183f040b632bd6e5e,

title = "An artificial immune system for self-healing in swarm robotic systems",

abstract = "Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we propose an approach to self-healing swarm robotic systems and take inspiration from the process of granuloma formation, a process of containment and repair found in the immune system. We use a case study of a swarm performing team work where previous works have demonstrated that partially failed robots have the most detrimental effect on overall swarm behaviour. In response this, we have developed an immune inspired approach that permits the recovery from certain failure modes during operation of the swarm, overcoming issues that effect swarm behaviour associated with partially failed robots.",

author = "Ismail, {Amelia R.} and Bjerknes, {Jan D.} and Jon Timmis and Alan Winfield",

year = "2015",

month = jan,

day = "1",

doi = "10.1007/978-3-319-23108-2_6",

language = "English",

isbn = "9783319231075",

volume = "9303",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "61--74",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

address = "Germany",

note = "10th International Conference on Information Processing in Cells and Tissues, IPCAT 2015 ; Conference date: 14-09-2015 Through 16-09-2015",

}

Ismail, AR, Bjerknes, JD, Timmis, J & Winfield, A 2015, An artificial immune system for self-healing in swarm robotic systems. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9303, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9303, Springer, pp. 61-74, 10th International Conference on Information Processing in Cells and Tissues, IPCAT 2015, San Diego, United Kingdom, 14/09/15. https://doi.org/10.1007/978-3-319-23108-2_6

An artificial immune system for self-healing in swarm robotic systems. / Ismail, Amelia R.; Bjerknes, Jan D.; Timmis, Jon et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9303 Springer, 2015. p. 61-74 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9303).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An artificial immune system for self-healing in swarm robotic systems

AU - Ismail, Amelia R.

AU - Bjerknes, Jan D.

AU - Timmis, Jon

AU - Winfield, Alan

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we propose an approach to self-healing swarm robotic systems and take inspiration from the process of granuloma formation, a process of containment and repair found in the immune system. We use a case study of a swarm performing team work where previous works have demonstrated that partially failed robots have the most detrimental effect on overall swarm behaviour. In response this, we have developed an immune inspired approach that permits the recovery from certain failure modes during operation of the swarm, overcoming issues that effect swarm behaviour associated with partially failed robots.

AB - Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we propose an approach to self-healing swarm robotic systems and take inspiration from the process of granuloma formation, a process of containment and repair found in the immune system. We use a case study of a swarm performing team work where previous works have demonstrated that partially failed robots have the most detrimental effect on overall swarm behaviour. In response this, we have developed an immune inspired approach that permits the recovery from certain failure modes during operation of the swarm, overcoming issues that effect swarm behaviour associated with partially failed robots.

UR - http://www.scopus.com/inward/record.url?scp=84945544579&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-23108-2_6

DO - 10.1007/978-3-319-23108-2_6

M3 - Conference contribution

AN - SCOPUS:84945544579

SN - 9783319231075

VL - 9303

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 61

EP - 74

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer

T2 - 10th International Conference on Information Processing in Cells and Tissues, IPCAT 2015

Y2 - 14 September 2015 through 16 September 2015

ER -

Ismail AR, Bjerknes JD, Timmis J, Winfield A. An artificial immune system for self-healing in swarm robotic systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9303. Springer. 2015. p. 61-74. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23108-2_6

An artificial immune system for self-healing in swarm robotic systems

Abstract

Publication series

Conference

Access to Document

Other files and links

Cite this