Developing a Simulation Model for Autonomous Driving Education in the Robobo SmartCity Framework

Abstract: This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.Ministerio de Ciencia, Innovación y Universidades of Spain/FEDER; t RTI2018-101114-B-I00 Erasmus+ Programme of the European Union; 2019-1-ES01-KA201-065742, Centro de Investigación de Galicia “CITIC”; ED431G 2019/01

Mecanum wheel robotic platform for educational purposes: a cost-effective approach

This paper presents a cost-effective approach of a mecanum wheel robotic platform for educational propose on the development of an autonomous or remote controlled mobile robot with a four-wheel mecanum drive train. The main structure of the mobile robot was developed in Solidworks and it was built using additive manufacturing to validate in a real scenario. The main objective of developing this type of mobile platform was the ability to transport different types of cargo or robotic arm on industrial spaces or on rough terrain, since the implemented suspension mechanism allows the wheels contact to the floor. Another important objective is the maneuverability and the capacity to be guided in various environments, a great advantage in this type of mobile platform. An additional advantage of the developed mobile robot is the easy way to reconfigure the structure for new acquired parts.The authors acknowledge the support of RD Unit SYSTEC-Base (UIDB/00147/2020) and Programmatic (UIDP/00147/2020) funds, and also the support of Project Warehouse of the Future (WoF), with reference POCI-01-0247-FEDER-072638, co-funded by European RegionalDevelopment Fund (ERDF), through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020)info:eu-repo/semantics/publishedVersio

Open hardware and software robotics competition for additional engagement in ECE students - the Robot@Factory lite case study

Throughout this paper, a competition created to enable an inter-connection between the academic and industrial paradigms is presented, using Open Hardware and Software. This competition is called Robot at Factory Lite and serves as a case study as an additional enrollment for students to apply knowledge in the fields of programming, perception, motion planning, task planning, autonomous robotic, among others.This work is financed by National Funds through the Portuguese funding agency, FCT- Fundação para a Ciência e a Tecnologia, with in project UIDB/50014/2020info:eu-repo/semantics/publishedVersio

The AutoDrive Challenge: Autonomous Vehicles Education and Training Issues

Automotive companies are focusing significant research and development efforts on autonomous vehicles. As they do so, they recognize the need for a large, well-trained workforce that is equipped to conduct these research and development projects, particularly in light of the projected shortages of STEM professionals in the United States. Some of these companies have found various ways to engage with professional societies and with universities to encourage the development of this workforce, and to promote themselves to STEM students while they are still in school. One such effort is the SAE / GM AutoDrive ChallengeTM, a new collegiate competition organized by SAE International in collaboration with General Motors Corporation. In this competition, eight teams are working to modify a Chevrolet Bolt to meet the requirements of a Level 4 autonomous vehicle (i.e., a vehicle that is totally capable of driving itself within a certain operational domain). Teams were selected for this competition through a proposal process, with one of the requested components of the proposal focusing on existing courses and the development of new courses at the participating university. In this paper, we will discuss the roles of students and faculty advisors at one of the participating schools, address issues related to education and training of students who want to work in the autonomous vehicle industry, and discuss the benefits of the competition to all of its stakeholders. This discussion will include the skills developed by students, the outcomes of the competition, and the value that is being created for the automotive industry. As part of this discussion, we will focus on the close ties that can be forged between the participating universities and the corporate sponsors of the AutoDrive Challenge, as well as the impact on course development at the universit

Desenvolvimento e validação de um simulador 3D para prova de condução autónoma do FNR

One of the more relevant research challenge competitions in the Festival Nacional de Robótica (FNR) is the Autonomous Driving Competition, where fully autonomous robots have to navigate in a complex scenario replicating road environments. Here robots must overcome challenges ranging from perception to navigation and control. In addition, there are challenges associated to the integration of sensors (Cameras, Inertial Measurement Unit (IMU), Laser and Encoders) able to support the navigation task or even at the mechanic development level, which sometimes, can be difficult to address by some research groups. Therefore, this paper presents a simulation environment developed for FNR Autonomous Driving Competition. This paper also covers various topics of mobile robotics, the proposed simulator is used in the development and validation of a location system, trajectory tracking, and obstacle avoidance.Inserida no Festival Nacional de Robótica (FNR), a prova Autonomous Driving Competition endereça desafios da condução autónoma, nesta competição os sistemas robóticos totalmente autónomos devem navegar num cenário de prova que retrata condições do ambiente rodoviário. Os robôs devem superar desafios relevantes da robótica móvel como a localização, percepção, navegação e controlo. São diversas as dificuldades e condicionalismos por parte dos participantes a este modelo de competição. A participação carece de uma solução de robô nem sempre disponível ou de fácil desenvolvimento e tende a integrar um considerável número de sensores. Esta dissertação apresenta um ambiente de simulação da prova de Condução Autónoma do FNR, sendo o simulador proposto utilizado no desenvolvimento e validação de um módulo de localização, path traking, path following e obstacle avoidance