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Modelling of a Group of Social Agents Monitored by UAVs

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Modelling and Simulation for Autonomous Systems (MESAS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10756))

Abstract

Robotics cooperation in service environments, i.e. environments shared with other non-robotic agents, is becoming more and more popular in industrial, agriculture, environmental monitoring and social applications. In this paper we propose a team of Unmanned Aerial Vehicles that has to control the trajectories of a group of agents having an internal behavioural logic, such as a group of human beings moving in a shared environment or an animal flocking. The controlling UAVs are assumed to generate a force on the group members, modelled as a repulsive force and representing some sort of “fear” of the flying robot. To this end, this paper proposes both an effective model for the group of agents, which is inspired by the Social Force Model, and a distributed estimation and control algorithm for the controlling UAVs. By means of simulations, the validity of the modelling and the control parts is shown and promising results are derived.

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Authors and Affiliations

  1. Department of Industrial Engineering, University of Trento, Via Sommarive, 9, 38122, Povo, Trento, Italy

    Federico Morelli, Davide Vignotto & Daniele Fontanelli

Authors
  1. Federico Morelli
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  2. Davide Vignotto
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  3. Daniele Fontanelli
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Corresponding author

Correspondence to Daniele Fontanelli .

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Editors and Affiliations

  1. NATO Modelling and Simulation Centre of Excellence, Rome, Italy

    Jan Mazal

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Morelli, F., Vignotto, D., Fontanelli, D. (2018). Modelling of a Group of Social Agents Monitored by UAVs. In: Mazal, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2017. Lecture Notes in Computer Science(), vol 10756. Springer, Cham. https://doi.org/10.1007/978-3-319-76072-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-76072-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76071-1

  • Online ISBN: 978-3-319-76072-8

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