Building a Flexible Mobile Robotics Teaching Toolkit by Extending MATLAB/Simulink with ROS and Gazebo

Niu, Yun; Qazi, Hafeezullah; Liang, Yalin

doi:10.1109/icmre51691.2021.9384836

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Niu et al [32] developed a toolkit for teaching mobile robotics through the Matlab™ and Simulink™ package add-on using ROS and the Gazebo simulator to improve learning efficiency in physical robotic simulation environments. Access to virtual sensors and actuators has been included in this toolkit, and communication details are hidden to allow students to focus on programming and debugging their autonomous driving algorithms.…”

Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

“…This activity was evaluated by measuring the time taken to complete a trajectory between the initial and final positions. The time obtained by each student was compared to find the best time [32].…”

Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

“…Its main components are the Python programming language, ROS Middleware, the Gazebo simulator, and a one-code template per exercise (Python ROS node and Jupyter Notebooks). This kit was used and validated in several undergraduate engineering courses at Rey Juan Carlos University in Niu et al [32] developed a toolkit for teaching mobile robotics through the Mat-lab™ and Simulink™ package add-on using ROS and the Gazebo simulator to improve learning efficiency in physical robotic simulation environments. Access to virtual sensors and actuators has been included in this toolkit, and communication details are hidden to allow students to focus on programming and debugging their autonomous driving algorithms.…”

Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

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A Free Simulation Environment Based on ROS for Teaching Autonomous Vehicle Navigation Algorithms

et al. 2022

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In recent years, engineering degree programs have become fundamental to the teaching of robotics and incorporate many fundamental STEM concepts. Some authors have proposed different platforms for teaching different topics related to robotics, but most of these platforms are not practical for classroom use. In the case of teaching autonomous navigation algorithms, the absence of platforms in classrooms limits learning because students are unable to perform practice activities or cannot evaluate and compare different navigation algorithms. The main contribution of this study is the implementation of a free platform for teaching autonomous-driving algorithms based on the Robot Operating System without the use of a physical robot. The authors present a case study using this platform as a teaching tool for instruction in two undergraduate robotic courses. Students evaluated the platform quantitatively and qualitatively. Our study demonstrates that professors and students can carry out different tests and compare different navigation algorithms to analyze their performance under the same conditions in class. In addition, the proposed platform provides realistic representations of environments and data visualizations. The results claim that the use of simulations helps students better understand the theoretical concepts, motivates them to pay attention, and increases their confidence.

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Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

Section: Using Ros To Teach Roboticsmentioning

confidence: 99%

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A Free Simulation Environment Based on ROS for Teaching Autonomous Vehicle Navigation Algorithms

et al. 2022

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“…El uso de estos programas para la simulación de robots está cada vez más extendido. Yun Niu [2] desarrolló una herramienta de simulación de robots móviles mediante los programas Matlab/Simulink, Gazebo y ROS. Este trabajo se centró más como material docente para el aprendizaje de nuevos algoritmos de guiado de robots.…”

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Modelado multiplataforma para el control de sistemas mecánicos

2022

Congreso Iberoamericano De Ingeniería Mecánica-Cibim 2022

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En el presente artículo se ha trabajado con las herramientas de simulación de sistemas mecánicos Gazebo y Simulink, realizando una interconexión entre ambos con el fin de desglosar la parte dinámica y cinemática de la parte de control, obtención y tratamiento de datos. La vía de enlace entre ambos programas se realiza mediante otro software de comunicación, ROS. Con todo ello, se ha conseguido la cosimulación de un mecanismo articulado en la cual, Simulink comanda trayectorias a Gazebo a través de pares en articulaciones, Gazebo envía los valores de posición articular de la simulación a Simulink, y mediante el control multiarticular de pares realimentados diseñado en este último programa, se minimiza el error entre la trayectoria simulada y la ideal. La obtención de los parámetros del modelo dinámico requeridos en el control se ha realizado mediante una librería de Matlab (Lib_3D_MEC_Matlab) de análisis de sistemas multicuerpo desarrollada por la UPNA.

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“…Gazebo offers the ability to simulate populations of robots accurately and efficiently in complex indoor and outdoor environments [63]. It is used in many research studies in the autonomous mobile robot field [64], [65], [66].…”

Section: B Gazebomentioning

confidence: 99%

Strategies for Cooperative Energy Distribution on Multi-Robot Warehouse Systems

Al-Gafari¹

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Autonomous mobile robots are one of the new and innovative ways to improve operation in industries such as warehouses, logistic companies, agricultural businesses, healthcare institutions, and a lot more. They are known for their operational improvement, safety, efficiency, and speed, automating several functionalities so they can be performed with little or no human intervention.These advantages can only be realized, however, if the degree of autonomy suffices for the task at hand. Whilst many degrees of autonomy exist (e.g., functional autonomy), in this thesis we are primarily concerned with an aspect of non-functional autonomy: energy. One of the important features of an autonomous robot system is the capability to charge autonomously with little to no human intervention. This thesis examines the energy distribution problem on multi-robot warehouse systems. We model warehouse systems where robots charge autonomously, pausing their workload when needed, to charge at a station. Depending on specific execution, it is possible that robots fully deplete their energy before arriving at a charging station, decreasing total work achieved, and becoming an obstacle on the warehouse floor. We then introduce the concept of energy sharing, where robots are capable of charging one another, essentially becoming mobile charging stations.In this context, the problem of energy distribution becomes a problem of multi-agent collaboration.We analyze the impact of our solution on a multi-agent simulation, showing that energy sharing for autonomous mobile robots in warehouse systems reduces the total number of depleted robots and contributes to increasing the amount of work performed.

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Building a Flexible Mobile Robotics Teaching Toolkit by Extending MATLAB/Simulink with ROS and Gazebo

Cited by 6 publications

References 8 publications

A Free Simulation Environment Based on ROS for Teaching Autonomous Vehicle Navigation Algorithms

A Free Simulation Environment Based on ROS for Teaching Autonomous Vehicle Navigation Algorithms

Modelado multiplataforma para el control de sistemas mecánicos

Strategies for Cooperative Energy Distribution on Multi-Robot Warehouse Systems

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