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Workshop of Physical Agents

WAF 2020: Advances in Physical Agents II pp 18–29Cite as

Lifelong Object Localization in Robotic Applications

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1285)

Abstract

One of the most common tasks in assistive robotics is to find some specific object in a home environment. Usually, this task is tackled by adding the objects of interest to a map of the environment as soon as the objects are detected by the vision system of the robot. However, these maps are usually static, and do not take into account the dynamic nature of a home, where anyone could move an object after the robot has seen it. In this paper, we propose a lifelong system to address this problem. The robot takes into account different possible locations for each object, and chooses the more probable one when it is required. We have designed a probability based system that stores possible locations for each object, and updates the probabilities of past locations based on newer detections.

Keywords

  • Image segmentation
  • Object detection
  • Robot vision
  • Deep learning

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  • DOI: 10.1007/978-3-030-62579-5_2
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Acknowledgments

This work has been partially sponsored by the Spanish Ministry of Science and Innovation under grant numbers TIN2016-77902-C3-1-P and PID2019-106758GB-C33, and by the Regional Council of Education, Culture and Sports of Castilla-La Mancha under grant number SBPLY/17/180501/000493, supported with FEDER funds.

Author information

Authors and Affiliations

  1. University of Castilla-La Mancha, Campus Univ. s/n, 02071, Albacete, Spain

    Cristina Romero-González, Jesus Martínez-Gómez & Ismael García-Varea

Authors
  1. Cristina Romero-González
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  2. Jesus Martínez-Gómez
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  3. Ismael García-Varea
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Corresponding author

Correspondence to Cristina Romero-González .

Editor information

Editors and Affiliations

  1. Electronics Department, University of Alcalá, Madrid, Spain

    Luis M. Bergasa

  2. Electronics Department, University of Alcalá, Madrid, Spain

    Manuel Ocaña

  3. Electronics Department, University of Alcalá, Madrid, Spain

    Rafael Barea

  4. Electronics Department, University of Alcalá, Madrid, Spain

    Elena López-Guillén

  5. Electronics Department, University of Alcalá, Madrid, Spain

    Pedro Revenga

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Romero-González, C., Martínez-Gómez, J., García-Varea, I. (2021). Lifelong Object Localization in Robotic Applications. In: Bergasa, L.M., Ocaña, M., Barea, R., López-Guillén, E., Revenga, P. (eds) Advances in Physical Agents II. WAF 2020. Advances in Intelligent Systems and Computing, vol 1285. Springer, Cham. https://doi.org/10.1007/978-3-030-62579-5_2

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