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Optimization is a very important issue to efficiently solve engineering problems. The clear comprehension of the elements and processes of optimizer algorithms is fundamental to ensure that engineer students are capable to apply, tune, and design new algorithms. This paper presents an educational platform based on LEGO© EV3 and MATLAB to assist the learning of the principles of classical and metaheuristic optimization algorithms at undergraduate level, by providing a simple and easy-to-follow teaching setup. The proposed study aims to accompany students through the learning of optimization fundamentals by building hands-on robotic experiments. The proposed educational platform has been successfully applied to several undergraduate courses within the Electronics Department at the University of Guadalajara. The description of each experiment and the evaluation of their impact in the student performance are both provided in the paper. [ABSTRACT FROM AUTHOR]

Fuzzy controllers have gained popularity in the past few decades with successful implementations in many fields that have enabled designers to control complex systems through linguistic-based rules in contrast to traditional methods. This paper presents an educational platform based on LEGO© NXT to assist the learning of fuzzy logic control principles at undergraduate level by providing a simple and easy-to-follow teaching setup. The proposed fuzzy control study aims to accustom students to the learning of fuzzy control fundamentals by building hands-on robotic experiments. The proposed educational platform has been successfully applied to several undergraduate courses within the Electronics Department in the University of Guadalajara. The description of robotic experiments and the evaluation of their impact on student performance are both provided in the paper. [ABSTRACT FROM AUTHOR]

In recent years, Artificial Intelligence (AI) techniques have emerged as useful nontraditional tools for solving various engineering problems. AI has thus become an important subject in the engineering curriculum. However, the design of a balanced AI course is not a trivial task as its concepts commonly overlap with many other disciplines relating a wide number of subjects and ranging from applied approaches to more formal mathematical issues. This paper presents the use of a simple robotic platform to assist the learning of basic AI concepts. The study is guided by simple experimentation on autonomous mobile robots. The presented material has been successfully tested as an AI teaching aid in the University of Guadalajara's robotics group, yielding motivation to students, increasing enrolment and retention on robotics-related courses and eventually contributing to the development of competent computer engineers. [ABSTRACT FROM AUTHOR]

This paper shows the potential of a LegoTM -based low-cost commercial robotic platform for learning and testing prototypes in higher education and research. The overall set-up aims to explain mobile robotic issues, including mechatronics, robotics and automatic control theory. The capabilities and limitations of Lego robots are studied within two experiments: the first shows how to eliminate a number of restrictions in Lego robots using some programming alternatives; the second addresses the complex problem of multi-position control. Algorithms and their additional tools have been fully designed, applied and documented, and the results are shown throughout the paper. The platform was found to be suitable for teaching and researching key issues related to the aforementioned fields. [ABSTRACT FROM AUTHOR]