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Simulation of Autonomous Robotic System for Intelligence and Reconnaissance Operations

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Modelling and Simulation for Autonomous Systems (MESAS 2022)

Abstract

This paper examines the possibilities of realistic simulations of robotic systems employed for intelligence and reconnaissance operations in the outdoor environment. Including simulation into the development process accelerates and facilitates testing, verification, and evaluation of algorithms, and prevents potential damage of expensive hardware. To achieve fast and flexible development, we utilize a widely used Robotic Operating System (ROS) framework, which, together with Gazebo simulator, enables to deploy robots and test algorithms in both real-world and simulation. Gazebo supports a wide range of customization options, including the creation of own worlds, robots, and sensors. Moreover, the solution allows to deploy a multiple heterogenous robots within one simulation instance to test cooperative missions. To demonstrate the potential of this simulation concept for intelligence operations, we introduce a scenario involving several flying and terrestrial robots during a Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) mission comprising a radiation source search. For this purpose, we deployed realistic robotic platforms into the aerial photogrammetry-based 3D world, and, above all, we improved the standard radiation plugin to collect credible data. The results indicate that the concept fulfills requirements for intelligence and reconnaissance robotic operation simulation.

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Acknowledgments

The research was funded from the Ministry of the Interior of the Czech Republic (MVCR) grant no. VJ02010036 (An Artificial Intelligence-Controlled Robotic System for Intelligence and Reconnaissance Operations).

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Correspondence to Petr Marcon .

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Cihlar, M. et al. (2023). Simulation of Autonomous Robotic System for Intelligence and Reconnaissance Operations. In: Mazal, J., et al. Modelling and Simulation for Autonomous Systems. MESAS 2022. Lecture Notes in Computer Science, vol 13866. Springer, Cham. https://doi.org/10.1007/978-3-031-31268-7_4

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  • DOI: https://doi.org/10.1007/978-3-031-31268-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31267-0

  • Online ISBN: 978-3-031-31268-7

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