Simulation Tools, Environments and Frameworks for UAV Systems Performance Analysis

Hentati, Aicha Idriss; Krichen, Lobna; Fourati, Mohamed; Fourati, Lamia Chaari

doi:10.1109/iwcmc.2018.8450505

Cited by 70 publications

(35 citation statements)

References 15 publications

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“…In the literature, there are numerous simulation proposals oriented to drone flight simulation modeling aspects such as mission planning and drone navigation and control. In [ 21 ], we find an analysis of the existing commercial tools such as X-plane, Flight Gear, JMavSim, or Microsoft AirSim. These tools allow realistically simulating drone flight and control in a synthetic three-dimensional environment that can be visualized by the user.…”

Section: Related Workmentioning

confidence: 99%

Sensors and Communication Simulation for Unmanned Traffic Management

Carramiñana

Campaña

Bergesio

et al. 2021

Sensors

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Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors’ behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots’ actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds.

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Section: Related Workmentioning

confidence: 99%

Sensors and Communication Simulation for Unmanned Traffic Management

Carramiñana

Campaña

Bergesio

et al. 2021

Sensors

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“…Modern UAV simulators allow researchers to replicate complex real-world environments by modelling turbulence, air density, wind shear, clouds, precipitation and other fluid mechanics constraints [90]. They also support various sensors -eg.…”

Section: Aerial Roboticsmentioning

confidence: 99%

A Review of Physics Simulators for Robotic Applications

Collins

Chand²,

Vanderkop³

et al. 2021

IEEE Access

116

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The use of simulators in robotics research is widespread, underpinning the majority of recent advances in the field. There are now more options available to researchers than ever before, however navigating through the plethora of choices in search of the right simulator is often non-trivial. Depending on the field of research and the scenario to be simulated there will often be a range of suitable physics simulators from which it is difficult to ascertain the most relevant one. We have compiled a broad review of physics simulators for use within the major fields of robotics research. More specifically, we navigate through key sub-domains and discuss the features, benefits, applications and use-cases of the different simulators categorised by the respective research communities. Our review provides an extensive index of the leading physics simulators applicable to robotics researchers and aims to assist them in choosing the best simulator for their use case.

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“…It provides a much more robust interface with many features such as NFZs and immersive 3D simulation. It runs on different platforms, namely, Windows, Mac OS, Ubuntu, iOS and Android devices [83].…”

Section: A Supported Ground Stationsmentioning

confidence: 99%

Micro Air Vehicle Link (MAVlink) in a Nutshell: A Survey

et al. 2019

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The micro air vehicle link (MAVLink in short) is a communication protocol for unmanned systems (e.g., drones and robots). It specifies a comprehensive set of messages exchanged between unmanned systems and ground stations. This protocol is used in major autopilot systems, mainly ArduPilot and PX4, and provides powerful features not only for monitoring and controlling unmanned systems missions but also for their integration into the Internet. However, there is no technical survey and/or tutorial in the literature that presents these features or explains how to make use of them. Most of the references are online tutorials and basic technical reports, and none of them presents comprehensive and systematic coverage of the protocol. In this paper, we address this gap, and we propose an overview of the MAVLink protocol, the difference between its versions, and it is potential in enabling Internet connectivity to unmanned systems. We also discuss the security aspects of the MAVLink. To the best of our knowledge, this is the first technical survey and tutorial on the MAVLink protocol, which represents an important reference for unmanned systems users and developers. INDEX TERMS MAVLink, ArduPilot, PX4, Unmanned Aerial Vehicles (UAVs), Ground Control Stations (GCSs).

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Simulation Tools, Environments and Frameworks for UAV Systems Performance Analysis

Cited by 70 publications

References 15 publications

Sensors and Communication Simulation for Unmanned Traffic Management

Sensors and Communication Simulation for Unmanned Traffic Management

A Review of Physics Simulators for Robotic Applications

Micro Air Vehicle Link (MAVlink) in a Nutshell: A Survey

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