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Position Estimation using the Radical Axis Gauss Newton Algorithm: Experimental Analysis

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Abstract

Generally unmanned aerial vehicles are currently equipped with multiple sensors to help them in their navigation. However, the acquisition of the position at every moment is a hard task to be achieved mainly in crowded scenarios where multiple obstacles make difficult the reception of signal coming from satellites (for global navigation systems) or base stations which perform the functions of anchors in some localization systems. Another issue in this kind of scenarios is the low probability to obtain redundancy systems due to the poor received signal associated to obstructions. For the case where there is only the minimum information required to estimate the position, the named radical axis Gauss Newton (RA-GN) algorithm was previously proposed and successfully evaluated by simulation. Now, in this paper, the RA-GN algorithm is applied to a localization system and evaluated experimentally from a measurement campaign conducted in a semi-forest test field. Moreover, we assess the effect of rotating the tag taken as the representation of the vehicle and found that this rotation introduces changes in the position estimation. All our results in terms of root mean square error are compared with those given by a commercial system. Results reported here show that the RA-GN algorithm is able to improve the accuracy of estimation of the commercial system in real conditions of crowded environments, even under complicated situations where the signal is perturbed by the obstacles and under different angular positions of the tag relative to the anchors.

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Acknowledgment

Authors want to thank the support given by Consejo Nacional de Ciencia y Tecnología (CONACYT), Mexico, through a postgraduate scholarship and the project 314879 “Laboratorio Nacional en Vehículos Autónomos y Exoesqueletos LANAVEX”.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. UMI LAFMIA Laboratory, Center for Research and Advanced Studies of IPN, Av. Instituto Politecnico Nacional 2508, Mexico City, 07360, Mexico

    Luis A. Arellano-Cruz & Rogelio Lozano

  2. Communications Section, Department of Electrical Engineering, Center for Research and Advanced Studies of IPN, Av. Instituto Politecnico Nacional 2508, Mexico City, 07360, Mexico

    Giselle M. Galvan-Tejada

  3. CNRS UMR Heudiasyc-UTC, Université de Technologie de Compiegne, Compiegne, 60203, France

    Rogelio Lozano

Authors
  1. Luis A. Arellano-Cruz
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  2. Giselle M. Galvan-Tejada
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  3. Rogelio Lozano
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Luis A. Arellano-Cruz, Giselle M. Galvan-Tejada and Rogelio Lozano. The first draft of the manuscript was written by Luis A. Arellano-Cruz and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Luis A. Arellano-Cruz.

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The authors have no relevant financial or non-financial interests to disclose.

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The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

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Luis A. Arellano-Cruz, Giselle M. Galvan-Tejada and Rogelio Lozano are contributed equally to this work.

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Arellano-Cruz, L.A., Galvan-Tejada, G.M. & Lozano, R. Position Estimation using the Radical Axis Gauss Newton Algorithm: Experimental Analysis. J Intell Robot Syst 107, 2 (2023). https://doi.org/10.1007/s10846-022-01779-x

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  • DOI: https://doi.org/10.1007/s10846-022-01779-x

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