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A Cell Potential and Motion Pattern Driven Multi-robot Coverage Path Planning Algorithm

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1159))

Abstract

This paper proposes an intelligent “Cell Potential and Motion Pattern driven Coverage (CPMPC)” algorithm to solve a cooperative coverage path planning problem for multiple robots in two-dimensional target environment. The target environment is divided into cell areas according to the detection range of robot, and the cell matrix is given correspondingly. The values in the cell matrix are defined as cell potential, which represents the number of times each cell is detected by robots. The priority of the robot’s neighbor cell is called the motion pattern. At different moments, robots can choose within different motion patterns. Genetic algorithm (GA) is used to optimize the combination of motion patterns. By taking account obstacle avoidance and collision avoidance into consideration, the CPMPC algorithm adopts a double-layer choice strategy driven by cell potential and motion pattern to generate the next waypoint. Furthermore, this algorithm contains two optimal strategies: avoiding collision and jumping out of the detected area. Compared with the pattern-based genetic algorithm, the results obtained by us show that the CPMPC algorithm could solve the multi-robot coverage path planning (MCPP) problem effectively with guarantee of complete coverage, and improved makespan.

This work was supported in part by the National Outstanding Youth Talents Support Program 61822304, the National Natural Science Foundation of China under Grant 61673058, the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization under Grant U1609214, the National Key R&D Program of China (2018YFB1308000).

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Authors and Affiliations

  1. School of Automation, State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, 100081, China

    Meng Xu, Bin Xin, Lihua Dou & Guanqiang Gao

Authors
  1. Meng Xu
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  2. Bin Xin
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  3. Lihua Dou
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  4. Guanqiang Gao
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Corresponding authors

Correspondence to Meng Xu or Bin Xin .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Xu, M., Xin, B., Dou, L., Gao, G. (2020). A Cell Potential and Motion Pattern Driven Multi-robot Coverage Path Planning Algorithm. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_36

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

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