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Assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation

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Robot 2023: Sixth Iberian Robotics Conference (ROBOT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 976))

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Abstract

Locating odour sources with mobile robots is a difficult task that can be applied to locating the sources of pollutants, concealed explosives or victims in disaster scenarios. The existing approaches for locating odour sources can be divided between those that simply seek to reach the chemical source, and those that use gas dispersion models to estimate its location. One of the most popular source estimation approaches is Infotaxis, which has been shown to have great sensitivity to the parameters of its gas distribution model.

In this paper, we compare two evolutionary approaches for automatically selecting the values for these parameters along with a Genetic Programming approach for evolving human-readable source-seeking strategies. The comparisons are carried out in three simulated environments with different chemical plumes and the results show that the parameters that best fit the environment do not always lead to the highest performance. Also, depending on the scenario, the tree-based search strategies are able to perform equivalently to Infotaxis, at a lesser computational cost.

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Acknowledgements

This work was supported by the Portuguese Foundation for Science and Technology, under projects UID/EEA/00048/2020 and UID/CEC/00326/2020, and by the Recovery and Resilience Plan (PRR) and by the European Funds Next Generation EU under Project “Agenda Mobilizadora Sines Nexus” (ref: 7113).

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Authors and Affiliations

  1. Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal

    João Macedo & Ernesto Costa

  2. Institute of Systems and Robotics, University of Coimbra, 3030 -290, Coimbra, Portugal

    Lino Marques

Authors
  1. João Macedo
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  2. Lino Marques
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  3. Ernesto Costa
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Corresponding author

Correspondence to João Macedo .

Editor information

Editors and Affiliations

  1. Dep. de Eng. Electrotecnica e de Computadores, University of Coimbra, Coimbra, Portugal

    Lino Marques

  2. Department of Electrónica Industrial, University of Minho, Escola de Engenharia, Guimarães, Portugal

    Cristina Santos

  3. Department of Electrical Engineering, Polytechnic Institute of Bragança, Bragança, Portugal

    José Luís Lima

  4. Centro Universitario de la Defensa, Zaragoza, Spain

    Danilo Tardioli

  5. Centre for Automation and Robotics UPM-CSIC, Universidad Politecnica de Madrid, Madrid, Spain

    Manuel Ferre

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Macedo, J., Marques, L., Costa, E. (2024). Assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-031-58676-7_14

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