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An extended analysis on tuning the parameters of Adaptive Monte Carlo Localization ROS package in an automated guided vehicle

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Abstract

With a growth tendency, the employment of the Adaptive Monte Carlo Localization (AMCL) Robot Operational System (ROS) package does not reflect a more in-depth discussion on its parameters’ tuning process. The authors usually do not describe it. This work aims to extend the analysis of the package’s parameters’ distinct influence in an automated guided vehicle (AGV) indoor localization. The experiments test parameters of the filter, the laser model, and the odometry model. Extending the previous analysis of seven parameters, the present research discusses another ten from the 22 configurable parameters of the package. An external visual vehicle pose tracking is used to compare the pose estimation from the localization package. Although the article does not propose the best parameter tuning, its results discuss how each tested parameter affects the localization. The paper’s contribution is discussing the parameters’ variation impact on the AGV localization using the covariance matrix results. It may help new researchers in the AMCL ROS package parameter tuning process. The results show minor changes in the default parameters which can improve the localization results, even modifying one parameter at a time.

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Acknowledgements

The authors thank the support of Capes, all the colleagues of TEAR Laboratory, and Dr. Abdeldjallil Naceri. The authors wish to extend special gratitude to Matheus Ungaretti Borges for kindly present the previous paper in ICAR 2019.

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Wallace dos Reis was financed in part by the Federal Institute of Education, Science and Tecnology of Rio de Janeiro—IFRJ, campus Volta Redonda.

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Authors and Affiliations

  1. TEAR - Laboratório de Estratégias de Automação e Robótica, Department of Computing, Federal University of São Carlos, São Paulo, SP, Brazil

    Wallace Pereira Neves dos Reis

  2. Federal Institute of Rio de Janeiro, campus Volta Redonda, Rio de Janeiro, RJ, Brazil

    Wallace Pereira Neves dos Reis

  3. PET-TEAR - Laboratório de Estratégias de Automação e Robótica, Department of Computing, Federal University of São Carlos, São Paulo, SP, Brazil

    Guilherme José da Silva

  4. Department of Computing, Federal University of São Carlos, São Paulo, SP, Brazil

    Orides Morandin Junior & Kelen Cristiane Teixeira Vivaldini

Authors
  1. Wallace Pereira Neves dos Reis
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  2. Guilherme José da Silva
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  3. Orides Morandin Junior
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  4. Kelen Cristiane Teixeira Vivaldini
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Correspondence to Wallace Pereira Neves dos Reis.

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Author contribution

Conceptualization: Wallace Pereira Neves dos Reis and Kelen Cristiane Teixeira Vivaldini. Methodology: Wallace Pereira Neves dos Reis, Kelen Cristiane Teixeira Vivaldini, and Orides Morandin Junior. Formal analysis and investigation: Wallace Pereira Neves dos Reis. Software and visualization: Wallace Pereira Neves dos Reis and Guilherme José da Silva. Writing—original draft preparation: Wallace Pereira Neves dos Reis. Writing—review and editing: Orides Morandin Junior. Resources: Kelen Cristiane Teixeira Vivaldini and Orides Morandin Junior. Supervision: Kelen Cristiane Teixeira Vivaldini and Orides Morandin Junior.

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Reis, W.P.N.d., Silva, G.J.d., Junior, O.M. et al. An extended analysis on tuning the parameters of Adaptive Monte Carlo Localization ROS package in an automated guided vehicle. Int J Adv Manuf Technol 117, 1975–1995 (2021). https://doi.org/10.1007/s00170-021-07437-0

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  • DOI: https://doi.org/10.1007/s00170-021-07437-0

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