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Performance Comparison of Visual Teach and Repeat Systems for Mobile Robots

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Modelling and Simulation for Autonomous Systems (MESAS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13866))

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Abstract

In practical work scenarios, it is often necessary to repeat specific tasks, which include navigating along a desired path. Visual teach and repeat systems are a type of autonomous navigation in which a robot repeats a previously taught path using a camera and dead reckoning. There have been many different teach and repeat methods proposed in the literature, but only a few are open-source. In this paper, we compare four recently published open-source methods and a Boston Dynamics proprietary solution embedded in a Spot robot. The intended use for each method is different, which has an impact on their strengths and weaknesses. When deciding which method to use, factors such as the environment and desired precision and speed should be taken into consideration. For example, in controlled artificial environments, which do not change significantly, navigation precision and speed are more important than robustness to environment variations. However, the appearance of unstructured natural environments varies over time, making robustness to changes a crucial property for outdoor navigation systems. This paper compares the speed, precision, reliability, robustness, and practicality of the available teach and repeat methods. We will outline their flaws and strengths, helping to choose the most suitable method for a particular utilization.

This research was funded by Czech Science Foundation research project number 20-27034J ‘ToltaTempo’.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, Czech Technical University, Prague, Czechia

    Maxim Simon, George Broughton, Tomáš Rouček, Zdeněk Rozsypálek & Tomáš Krajník

Authors
  1. Maxim Simon
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  2. George Broughton
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  3. Tomáš Rouček
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  4. Zdeněk Rozsypálek
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  5. Tomáš Krajník
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Corresponding author

Correspondence to Maxim Simon .

Editor information

Editors and Affiliations

  1. NATO M&S COE, Rome, Italy

    Jan Mazal

  2. University of Palermo, Palermo, Italy

    Adriano Fagiolini

  3. Brno University of Technology, Brno, Czech Republic

    Petr Vašík

  4. University of Genoa, Genova, Italy

    Agostino Bruzzone

  5. Bundeswehr University Munich, München, Germany

    Stefan Pickl

  6. University of Defence, Brno, Czech Republic

    Vlastimil Neumann

  7. University of Defence, Brno, Czech Republic

    Petr Stodola

  8. NATO Modelling & Simulation Centre of Ex, Rome, Italy

    Stefano Lo Storto

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Simon, M., Broughton, G., Rouček, T., Rozsypálek, Z., Krajník, T. (2023). Performance Comparison of Visual Teach and Repeat Systems for Mobile Robots. In: Mazal, J., et al. Modelling and Simulation for Autonomous Systems. MESAS 2022. Lecture Notes in Computer Science, vol 13866. Springer, Cham. https://doi.org/10.1007/978-3-031-31268-7_1

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  • DOI: https://doi.org/10.1007/978-3-031-31268-7_1

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