Voronoi-Based Multi-Robot Formations for 3D Source Seeking via Cooperative Gradient Estimation

In this paper, we tackle the problem of localizing the source of a three-dimensional signal field with a team of mobile robots able to collect noisy measurements of its strength and share information with each other. The adopted strategy is to cooperatively compute a closed-form estimation of the gradient of the signal field that is then employed to steer the multi-robot system toward the source location. In order to guarantee an accurate and robust gradient estimation, the robots are placed on the surface of a sphere of fixed radius. More specifically, their positions correspond to the generators of a constrained Centroidal Voronoi partition on the spherical surface. We show that, by keeping these specific formations, both crucial geometric properties and a high level of field coverage are simultaneously achieved and that they allow estimating the gradient via simple analytic expressions. We finally provide simulation results to evaluate the performance of the proposed approach, considering both noise-free and noisy measurements. In particular, a comparative analysis shows how its higher robustness against faulty measurements outperforms an alternative state-of-the-art solution.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icarcv63323.2024.10821664
Primary Topic
Robotics and Sensor-Based Localization
Type
article
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article

Voronoi-Based Multi-Robot Formations for 3D Source Seeking via Cooperative Gradient Estimation

Maryam Hamad, Alessandro Renzaglia, Lara Briñón-Arranz
Robotics and Sensor-Based Localization
article

Voronoi-Based Multi-Robot Formations for 3D Source Seeking via Cooperative Gradient Estimation

Maryam Hamad, Alessandro Renzaglia, Lara Briñón-Arranz
article en

Abstract

In this paper, we tackle the problem of localizing the source of a three-dimensional signal field with a team of mobile robots able to collect noisy measurements of its strength and share information with each other. The adopted strategy is to cooperatively compute a closed-form estimation of the gradient of the signal field that is then employed to steer the multi-robot system toward the source location. In order to guarantee an accurate and robust gradient estimation, the robots are placed on the surface of a sphere of fixed radius. More specifically, their positions correspond to the generators of a constrained Centroidal Voronoi partition on the spherical surface. We show that, by keeping these specific formations, both crucial geometric properties and a high level of field coverage are simultaneously achieved and that they allow estimating the gradient via simple analytic expressions. We finally provide simulation results to evaluate the performance of the proposed approach, considering both noise-free and noisy measurements. In particular, a comparative analysis shows how its higher robustness against faulty measurements outperforms an alternative state-of-the-art solution.

Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), GIPSA-Lab (FR), Institut National des Sciences Appliquées de Lyon (FR), Université Grenoble Alpes (FR)
Openalex Percentile: Top 58%
Robotics and Sensor-Based Localization
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