A Systematic Comparison of Simulation Software for Robotic Arm Manipulation using ROS2

Audonnet, Florent P.; Hamilton, A.; Aragon-Camarasa, Gerardo

doi:10.23919/iccas55662.2022.10003832

Cited by 14 publications

(3 citation statements)

References 45 publications

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“…V-REP is simpler to manage and edit objects, but a license is required [30]. Recently, Audonnet et al studied a robotic arm manipulation under different simulation software compatible with ROS 2 [31]. In this work, they give a comparison between Ignition and Webots in terms of stability and analyze PyBullet and Coppeliasim attending the resources usage.…”

Section: Of 16mentioning

confidence: 99%

Scalability of Cyber-Physical Systems in Mixed Reality Experiences in ROS 2

Mañas-Álvarez¹,

Guinaldo²,

Dormido³

et al. 2023

Preprint

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Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system's performance when the number of agents increases. To this end, two different mixed reality frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots being the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV those used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real-time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in mixed reality experiences regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

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Section: Of 16mentioning

confidence: 99%

Scalability of Cyber-Physical Systems in Mixed Reality Experiences in ROS 2

Mañas-Álvarez¹,

Guinaldo²,

Dormido³

et al. 2023

Preprint

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show abstract

“…In [47], ROS2 was proposed as a software framework to control the automation equipment of a reliable and robust automation system consisting of a motion control system (MCS) and an OpenPLC. A review of ROS2-compatible simulation software for manipulation with robotic arms, along with a comparison of them, can be found in [48]. A review highlighting the key changes of ROS2 in robotics is given in [49].…”

Section: Ros2: Industrial Robotics Applicationsmentioning

confidence: 99%

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Bonci,

Gaudeni,

Giannini

et al. 2023

Applied Sciences

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Future challenges in manufacturing will require automation systems with robots that are increasingly autonomous, flexible, and hopefully equipped with learning capabilities. The flexibility of production processes can be increased by using a combination of a flexible human worker and intelligent automation systems. The adoption of middleware software such as ROS2, the second generation of the Robot Operating System, can enable robots, automation systems, and humans to work together on tasks that require greater autonomy and flexibility. This paper has a twofold objective. Firstly, it provides an extensive review of existing literature on the features and tools currently provided by ROS2 and its main fields of application, in order to highlight the enabling aspects for the implementation of modular architectures to increase autonomy in industrial operations. Secondly, it shows how this is currently potentially feasible in ROS2 by proposing a possible high-level and modular architecture to increase autonomy in industrial operations. A proof of concept is also provided, where the ROS2-based framework is used to enable a cobot equipped with an external depth camera to perform a flexible pick-and-place task.

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“…V-REP is simpler to manage and makes it simpler to edit objects, but a license is required [34]. Recently, Audonnet et al studied a robotic arm manipulation under different simulation software compatible with ROS 2 [35]. In this work, they give a comparison between Ignition and Webots in terms of stability and analyze PyBullet and Coppeliasim attending the resources usage.…”

Section: Introductionmentioning

confidence: 99%

Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2

Mañas-Álvarez

Guinaldo

Dormido

et al. 2023

Sensors

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Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system’s performance when the number of agents increases. To this end, two different frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots, such as the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in experiences with real and virtual robots regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

show abstract

A Systematic Comparison of Simulation Software for Robotic Arm Manipulation using ROS2

Cited by 14 publications

References 45 publications

Scalability of Cyber-Physical Systems in Mixed Reality Experiences in ROS 2

Scalability of Cyber-Physical Systems in Mixed Reality Experiences in ROS 2

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2

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