### Abstract

In this paper, a multiple Cycle Sharing Algorithm (CSA) is proposed to solve the Multi-Robot Patrolling Problem (MRPP). In the MRPP, robots visit vertices in a graph continuously. The evaluation metric of the idleness of vertices is considered to evaluate the performance of an algorithm. Minimizing average graph idleness and the graph idleness standard deviation is covered because smaller average idleness means robots visit vertices more often, and smaller standard deviation of the graph idleness means robots visit vertices more regularly. The most effective way to minimize standard deviation is finding a Hamiltonian cycle in a graph. A Hamiltonian cycle visits each vertex exactly once, except for the vertex in which it starts and ends, thus visiting it twice. The solution to the Traveling Salesman Problem is known to minimize the cost of the corresponding Hamiltonian cycle. It is an NP-complete problem. If graph size becomes larger the longer time required for finding the minimum cost cycle; however, by partitioning the graph correctly into multiple sections with cooperative robots, the calculation time can be reduced remarkably.

Original language | English |
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Title of host publication | 2019 European Conference on Networks and Communications, EuCNC 2019 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 300-304 |

Number of pages | 5 |

ISBN (Electronic) | 9781728105468 |

DOIs | |

Publication status | Published - 2019 Jun |

Event | 28th European Conference on Networks and Communications, EuCNC 2019 - Valencia, Spain Duration: 2019 Jun 18 → 2019 Jun 21 |

### Publication series

Name | 2019 European Conference on Networks and Communications, EuCNC 2019 |
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### Conference

Conference | 28th European Conference on Networks and Communications, EuCNC 2019 |
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Country | Spain |

City | Valencia |

Period | 19/6/18 → 19/6/21 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Networks and Communications
- Hardware and Architecture
- Safety, Risk, Reliability and Quality

### Cite this

*2019 European Conference on Networks and Communications, EuCNC 2019*(pp. 300-304). [8802015] (2019 European Conference on Networks and Communications, EuCNC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EuCNC.2019.8802015

}

*2019 European Conference on Networks and Communications, EuCNC 2019.*, 8802015, 2019 European Conference on Networks and Communications, EuCNC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 300-304, 28th European Conference on Networks and Communications, EuCNC 2019, Valencia, Spain, 19/6/18. https://doi.org/10.1109/EuCNC.2019.8802015

**A Multi-Robot Cooperative Patrolling Algorithm with Sharing Multiple Cycles.** / Hong, Youngtaek; Kyung, Yeosun; Kim, Seong Lyun.

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

TY - GEN

T1 - A Multi-Robot Cooperative Patrolling Algorithm with Sharing Multiple Cycles

AU - Hong, Youngtaek

AU - Kyung, Yeosun

AU - Kim, Seong Lyun

PY - 2019/6

Y1 - 2019/6

N2 - In this paper, a multiple Cycle Sharing Algorithm (CSA) is proposed to solve the Multi-Robot Patrolling Problem (MRPP). In the MRPP, robots visit vertices in a graph continuously. The evaluation metric of the idleness of vertices is considered to evaluate the performance of an algorithm. Minimizing average graph idleness and the graph idleness standard deviation is covered because smaller average idleness means robots visit vertices more often, and smaller standard deviation of the graph idleness means robots visit vertices more regularly. The most effective way to minimize standard deviation is finding a Hamiltonian cycle in a graph. A Hamiltonian cycle visits each vertex exactly once, except for the vertex in which it starts and ends, thus visiting it twice. The solution to the Traveling Salesman Problem is known to minimize the cost of the corresponding Hamiltonian cycle. It is an NP-complete problem. If graph size becomes larger the longer time required for finding the minimum cost cycle; however, by partitioning the graph correctly into multiple sections with cooperative robots, the calculation time can be reduced remarkably.

AB - In this paper, a multiple Cycle Sharing Algorithm (CSA) is proposed to solve the Multi-Robot Patrolling Problem (MRPP). In the MRPP, robots visit vertices in a graph continuously. The evaluation metric of the idleness of vertices is considered to evaluate the performance of an algorithm. Minimizing average graph idleness and the graph idleness standard deviation is covered because smaller average idleness means robots visit vertices more often, and smaller standard deviation of the graph idleness means robots visit vertices more regularly. The most effective way to minimize standard deviation is finding a Hamiltonian cycle in a graph. A Hamiltonian cycle visits each vertex exactly once, except for the vertex in which it starts and ends, thus visiting it twice. The solution to the Traveling Salesman Problem is known to minimize the cost of the corresponding Hamiltonian cycle. It is an NP-complete problem. If graph size becomes larger the longer time required for finding the minimum cost cycle; however, by partitioning the graph correctly into multiple sections with cooperative robots, the calculation time can be reduced remarkably.

UR - http://www.scopus.com/inward/record.url?scp=85071721741&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071721741&partnerID=8YFLogxK

U2 - 10.1109/EuCNC.2019.8802015

DO - 10.1109/EuCNC.2019.8802015

M3 - Conference contribution

AN - SCOPUS:85071721741

T3 - 2019 European Conference on Networks and Communications, EuCNC 2019

SP - 300

EP - 304

BT - 2019 European Conference on Networks and Communications, EuCNC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -