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Multi-robot Path Planning for Complete Coverage with Genetic Algorithms

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Intelligent Robotics and Applications (ICIRA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11744))

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Abstract

Complete coverage path planning (CPP) generates a path following which a robot can cover all free spaces in an environment. Compared with single robot CPP, multi-robot CPP gains both efficiency and challenges. In large scale environments, one robot is not competent to the coverage task, such as doing cleaning work in airports, supermarkets, shopping malls, etc. The proposed approach firstly creates a global map with a simultaneous localization and mapping (SLAM) method, and partitions the map into a set of small sub-regions according to the environment’s topological structure. Then the multi-robot CPP formed a multiple traveling salesman (mTSP) problem, where a genetic algorithm (GA) allocates the sub-regions to each robot and gives the robots their visiting orders to the sub-regions. This paper mainly focuses on how to model the multi-robot CPP problem with mTSP and how to solve the task allocation problem with an improved GA algorithm off-line. Two SLAM-based environmental experiments validated the proposed method’s feasibility and efficiency in terms of time consumption.

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Authors and Affiliations

  1. School of Mechanical and Electric Engineering, Soochow University, Suzhou, China

    Rongchuan Sun, Chunhua Tang, Yongzheng Zhou & Shumei Yu

  2. School of Rail Transportation, Soochow University, Suzhou, China

    Jianying Zheng

Authors
  1. Rongchuan Sun
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  2. Chunhua Tang
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  3. Jianying Zheng
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  4. Yongzheng Zhou
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  5. Shumei Yu
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Corresponding author

Correspondence to Shumei Yu .

Editor information

Editors and Affiliations

  1. Shenyang Institute of Automation, Shenyang, China

    Haibin Yu

  2. Shenyang Institute of Automation, Shenyang, China

    Jinguo Liu

  3. Shenyang Institute of Automation, Shenyang, China

    Lianqing Liu

  4. University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  5. Shenyang Institute of Automation, Shenyang, China

    Yuwang Liu

  6. University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Sun, R., Tang, C., Zheng, J., Zhou, Y., Yu, S. (2019). Multi-robot Path Planning for Complete Coverage with Genetic Algorithms. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11744. Springer, Cham. https://doi.org/10.1007/978-3-030-27541-9_29

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  • DOI: https://doi.org/10.1007/978-3-030-27541-9_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27540-2

  • Online ISBN: 978-3-030-27541-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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