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Learning Robotics: a Review

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Purpose of Review With the growing interest for STEM/STEAM, new robotic platforms are being created with different characteristics, extras, and options. There are so many diverse solutions that it is difficult for a teacher/student to choose the ideal one. This paper intends to provide an analysis of the most common robotic platforms existent on the market. The same is happening regarding robotic events all around the world, with objectives so distinctive, and with complexity from easy to very difficult. This paper also describes some of those events which occur in many countries. Recent Findings As the literature is showing, there has been a visible effort from schools and educators to teach robotics from very young ages, not only because robotics is the future, but also as a tool to teach STEM/STEAM areas. But as time progresses, the options for the right platforms also evolve making difficult to choose amongst them. Some authors opt to first choose a robotic platform and carry on from there. Others choose first a development environment and then look for which robots can be programmed from it. Summary An actual review on learning robotics is here presented, firstly showing some literature background on history and trends of robotic platforms used in education in general, the different development environments for robotics, and finishing on competitions and events. A comprehensive characterization list of robotic platforms along with robotic competitions and events is also shown.
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ROBOTICS IN MANUFACTURING (JN PIRES, SECTION EDITOR)
Learning Robotics: a Review
A.Fernando Ribeiro
1
&Gil Lopes
1
Published online: 18 January 2020
#Springer Nature Switzerland AG 2020
Abstract
Purpose of Review With the growing interest for STEM/STEAM, new robotic platforms are being created with different
characteristics, extras, and options. There are so many diverse solutions that it is difficult for a teacher/student to choose the
ideal one. This paper intends to provide an analysis of the most common robotic platforms existent on the market. The same is
happening regarding robotic events all around the world, with objectives so distinctive, and with complexity from easy to very
difficult. This paper also describes some of those events which occur in many countries.
Recent Findings As the literature is showing, there has been a visible effort from schools and educators to teach robotics from
very young ages, not only because robotics is the future, but also as a tool to teach STEM/STEAM areas. But as time progresses,
the options for the right platforms also evolve makingdifficult to choose amongst them. Some authors opt to first choose a robotic
platform and carry on from there. Others choose first a development environment and then look for which robots can be
programmed from it.
Summary An actual review on learning robotics is here presented, firstly showing some literature background on history and
trends of robotic platforms used in education in general, the different development environments for robotics, and finishing on
competitions and events. A comprehensive characterization list of robotic platforms along with robotic competitions and events is
also shown.
Keywords Distribution .STEM/STEAM .Educational robotics .Robotic platforms .Mobile robotics .Autonomous robotics .
K12
Introduction
Robotics in the past was considered rocket science created by
scientists or high-skilled engineers. Nowadays, that is not the
case anymore. The importance of learning robotics especially
at early ages is visible by the amount of studies found in the
literature. Although robotics started as machines that perform
routine or dangerous tasks previously done by humans, it has
evolved to autonomous and mobile robotics and lately is used
to help improve students knowledge and skills in science,
technology, engineering, and mathematics (STEM). Arts
was another area that took the opportunity to embrace robotics
and thus the acronym became STEAM [1].
Kindergarten is the childs first school, and Evgenia
Roussou successfully introduced computational thinking by
playing with robotics at these childrenslevel[2].
At the primary school level, a similar approach was
experimented [3]. The focus was on the teacherssideprovid-
ing them with a robotic kit to promote problem-solving and
group work with their pupils. Teachers felt more confident and
aware of teaching computational thinking concepts. Another
study in primary schools was performed to introduce educa-
tional robotics (ER) by using a realistic mathematics approach
[4]. Students motivation was higher when compared with
learning mathematics in a traditional way. At the K-12 level,
in order to motivate students enrolling in technology areas,
one school used their Project Area curricular unit to have
groups of students participating in the RoboParty® event
[5]. A standard robotics curriculum for K-16 students was
proposed by Carlotta et al. [6] where a set of guiding
A.Fernando Ribeiro and Gil Lopes contributed equally to this work.
This article is part of theTopical Collection on Robotics in Manufacturing
*A.Fernando Ribeiro
fernando@dei.uminho.pt
Gil Lopes
gil@dei.uminho.pt
1
Department of Industrial Electronics and Algoritmi Research Centre,
University of Minho, Campus de Azurém,
4800-058 Guimarães, Portugal
Current Robotics Reports (2020) 1:111
https://doi.org/10.1007/s43154-020-00002-9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... The combination of these elements with advanced software such as Robot Operating System (ROS) and artificial intelligence paradigms allows students to carry out specific applications in everyday situations (Abdiakhmetova et al., 2024;Hernández-León & Rodríguez-Conde, 2024). Studies exploring the impact of robotics in the classroom (Adnan et al., 2023;Darmawansah et al., 2023;Kyprianou et al., 2023;Lin & Chen, 2023;Mangina et al., 2023;Ribeiro & Lopes, 2020), underline the importance of these technologies in enhancing learning in STEM areas. Educational robotics not only helps students develop technical skills such as programming, but also promotes critical thinking and creativity (Avello-Martínez et al., 2020) and the inclusion of robotics kits in the classroom provides students with hands-on experiences where there is no single correct solution, thus encouraging the exploration of multiple approaches to solving problems; this enriches students' cognitive skills and fosters collaboration in the classroom. ...
... This is achieved through advanced communication protocols between robots and the use of controllers such as Arduino, allowing the creation of multi-agent systems (Najjar et al., 2019). Robotics also contributes positively to students' motivation (Ribeiro & Lopes, 2020) by adapting to different educational levels (Mamatnabiyev et al., 2024) to apply abstract concepts in practical contexts, which improves their understanding of emerging technologies. ...
... This teaching strategy improves both attention and academic performance (Dochshanov & Tramonti, 2023;Mangina et al., 2023). Learning experiences with Arduino also result in high levels of satisfaction for both students and teachers (Ribeiro & Lopes, 2020). ...
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... Specifically, it involves knowledge of programming, electronics, design, and fabrication; thus, critical thinking and problemsolving stimulation are inevitable. Moreover, robotic competitions help train and motivate young students in STEM education as the engagement provides stimuli to solve tangible societal problems [3][4][5][6]. The practice of competitions and prizes in an undergraduate course effectively stimulates ingenuity and innovation to ascertain defined educational outcomes. ...
... A continuación, la plataforma robótica realiza un registro de sus acciones, dependiendo de sus características y funciones particulares (Ribeiro & Lopes, 2020). Para ello, dicha plataforma puede ser apoyada por su desarrollador, quien le dará el "feedback" respectivo para cada uno de sus actos, de la misma manera como cuando se refuerza una conducta animal o humana (Calderone, 2017). ...
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... Middle school students are often the focus of these investigations within the context of drone and robotics activities, as research has shown that students at this age-range start to develop interests in STEM and begin to consider career aspirations (Almeda & Baker, 2020). To engage middle school students, drone and robotics education leverages extracurricular events such as competitions, workshops, and after-school programs (Ribeiro & Lopes, 2020). These events have been successfully implemented in a limited number of STEM disciplines (e.g., computer science, mathematics) to increase motivation and engagement (Chou, 2018;Bartholomew & Mayo, 2018) as well as self-efficacy and interest (Tezza et al., 2020). ...
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... Collaborative robotic learning, which takes place with computer support, contributes not only to learning, a robotic app is a motivating activity for students that fosters collaboration between them, has a positive effect on learning and the emotional state of students, when a synergistic effect can be observed between participants in the educational process (Tang et al., 2020;Kerimbayev et al., 2020;Ribeiro & Lopes, 2020;Yang et al., 2020;Ospennikova et al., 2015;Lubold et al., 2021). ...
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... However, the application of robotic simulations must support transfer to the real robot to test the students' work in real devices and face the issues that arise when moving from simulation to reality, which is still an open issue for pre-university levels [34]. Table I details the previous features in 9 of the most relevant educational robots in the market [35] [36]. They are organized into three main groups. ...
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The main goal of this paper is to analyze the general problem of using Convolutional Neural Networks (CNNs) in robots with limited computational capabilities, and to propose general design guidelines for their use. In addition, two different CNN based NAO robot detectors that are able to run in real-time while playing soccer are proposed. One of the detectors is based on the XNOR-Net and the other on the SqueezeNet. Each detector is able to process a robot object-proposal in ~1 ms, with an average number of 1.5 proposals per frame obtained by the upper camera of the NAO. The obtained detection rate is ~97%. KeywordsDeep learningConvolutional Neural NetworksRobot detection