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Swarming Out of the Lab: Comparing Relative Localization Methods for Collective Behavior

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Swarm Intelligence (ANTS 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14987))

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Abstract

Efficient collaboration within a robot swarm hinges on the precise localization of swarm members relative to their neighbors. However, in real-world scenarios, such as indoor GPS-denied environments, access to accurate global localization systems is typically limited, and relative localization poses challenges due to the absence of a global reference frame. This paper compares the localization accuracy of three methods: IR-based, visual-inertial, and ultra-wideband localization systems. We evaluate these systems to ascertain the relative localization accuracy of neighboring robots engaged in collective behaviors. We develop a simulation model for the three localization systems and conduct accuracy studies. Furthermore, we deploy two swarms, one consisting of five flying robots and one consisting of five ground robots performing three distinct behaviors to validate the simulation experiments. Through simulation and robot experiments, we present the characteristics of each system, including estimation accuracy, deployment cost, communication overhead, and behavior performance accuracy.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, Canada

    Rafael Gomes Braga & David St-Onge

  2. Computer and Software Engineering Department, Polytechnique Montréal, Montreal, Canada

    Vivek Shankar Varadharajan & Giovanni Beltrame

Authors
  1. Rafael Gomes Braga
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  2. Vivek Shankar Varadharajan
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  3. Giovanni Beltrame
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  4. David St-Onge
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Corresponding author

Correspondence to Rafael Gomes Braga .

Editor information

Editors and Affiliations

  1. University of Konstanz, Konstanz, Germany

    Heiko Hamann

  2. IRIDIA, Université Libre de Bruxelles, Brussels, Belgium

    Marco Dorigo

  3. Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile

    Leslie Pérez Cáceres

  4. University of Konstanz, Konstanz, Germany

    Andreagiovanni Reina

  5. University of Konstanz, Konstanz, Germany

    Jonas Kuckling

  6. University of Technology Nuremberg, Nuremberg, Germany

    Tanja Katharina Kaiser

  7. University of Southampton, Southampton, UK

    Mohammad Soorati

  8. Royal Military Academy, Brussels, Belgium

    Ken Hasselmann

  9. University of Konstanz, Konstanz, Germany

    Eduard Buss

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Braga, R.G., Varadharajan, V.S., Beltrame, G., St-Onge, D. (2024). Swarming Out of the Lab: Comparing Relative Localization Methods for Collective Behavior. In: Hamann, H., et al. Swarm Intelligence. ANTS 2024. Lecture Notes in Computer Science, vol 14987. Springer, Cham. https://doi.org/10.1007/978-3-031-70932-6_14

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  • DOI: https://doi.org/10.1007/978-3-031-70932-6_14

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