For almost 25 years, the goal of the RoboCup has been to build soccer robots capable of winning against the FIFA World Champion of 2050. To foster the participation of the next generation of roboticists, the RoboCupJunior competition takes place in parallel and provides a similar challenge of appropriate difficulty for high school students. RoboCupJunior has three main categories: Soccer, Rescue and OnStage. For the Soccer category, participants need to design, build and program a team of autonomous robots to play soccer against an opponent team of robots. The competition is physical in nature, since it assumes physical robots playing against one another. In 2020 and 2021, the COVID-19 pandemic has made it difficult for a competition of this type to take place, due to obvious restrictions on physical gatherings. To allow for some sort of participation, and inspired by positive experience of the larger RoboCup community, the Organizing Committee of RoboCupJunior Soccer has explored porting a portion of the challenge to a simulated environment. Many of the existing environments, however, are built for higher education/research teams competitions or research, making them complex to deploy and generally unsuitable for high school students. In this paper we present the development of SoccerSim, a simulated environment for RoboCupJunior Soccer, based on the Webots open-source robotics simulator. We also discuss how the participation of students was key for its development and present a summary of the competition rules. We further describe the case study of utilizing SoccerSim first as a testbed for a Demo competition, and later as part of RoboCup Worldwide 2021. The participation of more than 60 teams from over 20 countries suggests that SoccerSim provides an affordable alternative to physical robotics platforms, while being stable enough to support a diverse userbase. The experience of using SoccerSim at RoboCupJunior Worldwide 2021 suggests that a simulated environment significantly lowers the barrier to entry, as evidenced by the participation of many teams that have not participated before. To make it easy for similar competitions to take place in the future, we made the code of SoccerSim available as open-source, as well as the associated tooling required for using it in a tournament.
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The use of robots as educational tools provides a stimulating environment for students. Some robotics competitions focus on primary and secondary school aged children, and serve as motivation for students to get involved in educational robotics activities. Although very appealing, many students cannot participate on robotics competitions because they cannot afford robotics kits. Hence, several students have no access to educational robotics, especially on developing countries. To minimize this problem and contribute to education equality, we have created RoSoS Robot Soccer Simulator, in which students program virtual robots in a similar way that they would program their real ones. In this chapter we explain some technical details of RoSoS and discuss the implementation of a new league for the robotics competitions: Junior Soccer Simulation league (JSS). Because soccer is the most popular sport in the world, we believe JSS will be a strong motivator for students to get involved with robotics.
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The use of robots as educational tools provide a stimulating environment for students. Some robotics competitions focus on primary and secondary school aged children, and serve as a motivation factor for students to get involved in educational robotics activities. But, in most competitions students are required to deal with robot design, construction and programming. Although very appealing, many students cannot participate on robotics competitions because they cannot afford robotics kits and their school do not have the necessary equipment. Because of that, several students have no access to educational robotics, especially on developing countries. To minimize this problem and contribute to education equality, we present a proposal for a new league for the robotics competitions: The Junior Soccer Simulation league (JSS). In such a league, students program virtual robots in a similar way that they would program their real ones. Because there is no hardware involved, costs are very low and participants can concentrate on software development and robot's intelligence improvement. Finally, because soccer is the most popular sport in the world, we believe JSS will be a strong motivator for students to get involved with robotics. In this paper we present the simulator that was developed (ROSOS) and discuss some ideas for the adoption of a Junior Soccer Simulation competition.
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This study investigates what pupils aged 10-12 can learn from working with robots, assuming that understanding robotics is a sign of technological literacy. We conducted cognitive and conceptual analysis to develop a frame of reference for determining pupils' understanding of robotics. Four perspectives were distinguished with increasing sophistication; psychological, technological, function, and controlled system. Using Lego Mindstorms NXT robots, as an example of a Direct Manipulation Environment, we developed and conducted a lesson plan to investigate pupils' reasoning patterns. There is ample evidence that pupils have little difficulty in understanding that robots are man-made technological and functional artifacts. Pupils' understanding of the controlled system concept, more specifically the complex sense-reason-act loop that is characteristic of robotics, can be fostered by means of problem solving tasks. The results are discussed with respect to pupils' developing technological literacy and the possibilities for teaching and learning in primary education.
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Localization is a crucial skill in mobile robotics because the robot needs to make reasonable navigation decisions to complete its mission. Many approaches exist to implement localization, but artificial intelligence can be an interesting alternative to traditional localization techniques based on model calculations. This work proposes a machine learning approach to solve the localization problem in the RobotAtFactory 4.0 competition. The idea is to obtain the relative pose of an onboard camera with respect to fiducial markers (ArUcos) and then estimate the robot pose with machine learning. The approaches were validated in a simulation. Several algorithms were tested, and the best results were obtained by using Random Forest Regressor, with an error on the millimeter scale. The proposed solution presents results as high as the analytical approach for solving the localization problem in the RobotAtFactory 4.0 scenario, with the advantage of not requiring explicit knowledge of the exact positions of the fiducial markers, as in the analytical approach.
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Accurate localization in autonomous robots enables effective decision-making within their operating environment. Various methods have been developed to address this challenge, encompassing traditional techniques, fiducial marker utilization, and machine learning approaches. This work proposes a deep-learning solution employing Convolutional Neural Networks (CNN) to tackle the localization problem, specifically in the context of the RobotAtFactory 4.0 competition. The proposed approach leverages transfer learning from the pre-trained VGG16 model to capitalize on its existing knowledge. To validate the effectiveness of the approach, a simulated scenario was employed. The experimental results demonstrated an error within the millimeter scale and rapid response times in milliseconds. Notably, the presented approach offers several advantages, including a consistent model size regardless of the number of training images utilized and the elimination of the need to know the absolute positions of the fiducial markers.
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From the pubisher's website: This paper aims to chart the (moral) values from a robotic industry's perspective regarding the introduction of robots in education. To our knowledge, no studies thus far have addressed this perspective in considering the moral values within this robotic domain. However, their values could conflict with the values upheld by other relevant stakeholders, such as the values of teachers, parents or children. Hence, it is crucial to take the various perspectives of relevant stakeholder's moral values into account. For this study, multiple focus group sessions (n=3) were conducted in The Netherlands with representatives (n=13) of robotic companies on their views of robots in primary education. Their perceptions in terms of opportunities and concerns, were then linked to business values reported in the extant literature. Results show that out of 26 business values, mainly six business values appeared relevant for robot tutors: 1) profitability, 2) productivity, 3 & 4) innovation and creativity, 5) competitiveness, and 6) risk orientation organization. https://doi.org/10.1109/DEVLRN.2019.8850726
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Described are a number of national and local initiatives that are taken to motivate young people to choose for technical education. From the local initiatives we focus on the area where Fontys and Actemium are located; the southeast of the Netherlands. Not only governmental organizations and foundations are active in this field but also (industrial) companies become more aware of the fact that creating interest for professions in technology should start at the earliest possible age. History shows that initiatives become more effective when not only directed to promotion, but accompanied by appropriate projects. We conclude with an example of a technology event and a discussion of the effectiveness of the initiatives.
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