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Socially Acceptable Navigation of People with Multi-robot Teams

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Abstract

Socially acceptable navigation is a subject that involves developments regarding Human-Robot Interaction (HRI) and autonomous mobile robot navigation. In this context, there is little research considering people interacting with a robot team, and even fewer considering multi-robot teams with people. In this paper, a study on socially acceptable navigation involving a human and a robot team is presented. Four navigation strategies that consider social aspects are presented and compared in simulated environment by terms as the average number of robots invading the personal space and the number of robots to the person’s side, with two of them using Asymmetric Gaussian Functions (AGFs) as the person’s social zone model; a navigation perception comparison is made involving people to investigate their view on navigating with three robots in contrast to a single robot. Simulated and real-world experiments were performed showing that the proposed methods have advantages over each other on different aspects. The follow-up techniques for interaction between humans and a team of robots suggest that people’s perception may not be affected significantly when interacting with more than one robot.

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Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Authors and Affiliations

  1. Institute of Mathematics and Computer Sciences, São Paulo University, São Carlos, SP, Brazil

    Murillo Rehder Batista & Roseli Aparecida Francelin Romero

  2. Computer Vision and Robotics Laboratory (VeRLab), Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Douglas Guimarães Macharet

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  1. Murillo Rehder Batista
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  2. Douglas Guimarães Macharet
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  3. Roseli Aparecida Francelin Romero
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Correspondence to Murillo Rehder Batista.

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Batista, M.R., Macharet, D.G. & Romero, R.A.F. Socially Acceptable Navigation of People with Multi-robot Teams. J Intell Robot Syst 98, 481–510 (2020). https://doi.org/10.1007/s10846-019-01080-4

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  • DOI: https://doi.org/10.1007/s10846-019-01080-4

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