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.
This paper addresses an approach to teaching embedded systems programming through a challenge-based competition involving robots. This pedagogical project distinguishes itself by incorporating international students from three international institutions through the Blended Intensive Program (BIP). The research findings indicate that this approach yields excellent results regarding student engagement and learning outcomes. The challenge-based program effectively promotes students' creative problem-solving abilities by combining theoretical instruction with hands-on experience in a competitive setting.
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
