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An Improved Single Robot SLAM Algorithm Based on Particle Filter

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Proceedings of the 12th International Conference on Computer Engineering and Networks (CENet 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 961))

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Abstract

Robot simultaneous localization and mapping is the basis of robot intelligence. When using lidar sensor to identify the external environment, the movement of the robot will cause lidar motion distortion. On the basis of analyzing SLAM algorithm of single robot based on particle filter, odometer assisted lidar is added to remove motion distortion. A comparative simulation experiment is carried out on Gazebo simulation platform. The experimental results show that the improved SLAM algorithm can effectively remove the motion distortion of lidar and improve the accuracy of image construction.

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Authors and Affiliations

  1. School of Electrical Engineering, University of Jinan, Jinan, 250022, China

    Ge Ge, Yong Zhang & Zhiping Xu

Authors
  1. Ge Ge
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  2. Yong Zhang
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  3. Zhiping Xu
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Corresponding author

Correspondence to Yong Zhang .

Editor information

Editors and Affiliations

  1. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Qi Liu

  2. School of Computing, Edinburgh Napier University, Edinburgh, UK

    Xiaodong Liu

  3. School of Computer Science and Technology, Hainan University, Haikou, Hainan, China

    Jieren Cheng

  4. School of Electrical Engineering, University of Jinan, Jinan, Shandong, China

    Tao Shen

  5. School of Computer Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, China

    Yuan Tian

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ge, G., Zhang, Y., Xu, Z. (2022). An Improved Single Robot SLAM Algorithm Based on Particle Filter. In: Liu, Q., Liu, X., Cheng, J., Shen, T., Tian, Y. (eds) Proceedings of the 12th International Conference on Computer Engineering and Networks. CENet 2022. Lecture Notes in Electrical Engineering, vol 961. Springer, Singapore. https://doi.org/10.1007/978-981-19-6901-0_92

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  • DOI: https://doi.org/10.1007/978-981-19-6901-0_92

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-6900-3

  • Online ISBN: 978-981-19-6901-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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