Updating the Content of an AI Course for Students from the Robotics and Automation
Abstract
The impact of artificial intelligence applications in today’s society is constantly growing. In this context, it is important to adapt the curricula of artificial intelligence courses with an emphasis on the practical applicability of new concepts and methods. At the University of Craiova, Romania, such a course is offered to undergraduate students in Robotics and Automation. The course includes chapters dedicated to problem solving, fuzzy logic, neural networks, and expert systems, with the identification of techniques related to the representation of knowledge and deep learning, respectively. This paper will present how to update the chapter on deep learning, referring to practical applications developed by groups of teachers, researchers and students from the faculty. The following applications are considered. An application is related to the management of a mobile robot that helps people with special needs in terms of control of the lower and upper limbs but who also have specific problems related to their visual system. Another application refers to the use of artificial intelligence techniques in applications for detecting casting defects in car engines. Another chapter that is to be introduced in the course refers to bots - cooperative software robots. The introduction of this chapter is also related to the international presence of an important number of highly successful companies that have been established by Romanian entrepreneurs. The three applications are demonstrated during the practical classes of the artificial intelligence course. Latest hardware platforms (i.e. nVidia Jetson Nano development boards) are used, and trending development environments, languages (Python, C++), and libraries (Numpy, Pandas, Matplotlib, SciKits) are implied. The inclusion of the presentation of these practical applications aims to increase the students' confidence that the knowledge received increases not only their level of theoretical knowledge, but also their chances of being hired by local companies that carry out activities in the field.
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Some commonly identified challenges include the complexity of the AI knowledge, a reliance on programming skills, and targeting senior undergraduate students, collectively indicating a low accessibility.
“Some commonly identified challenges include the complexity of the AI knowledge, a reliance on programming skills, and targeting senior undergraduate students [25], [41], [43], collectively indicating a low accessibility.”
From Integrating AI in engineering education: A comprehensive review and student-informed module design for U.K. students (2025) · cites this paper as [41]
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Self-citationInterdisciplinary Technical Competitions – A Case Study
Dragomir, A., Manta, L. F., Mariniuc, A. M., & Cojocaru, D. (2021) · Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE) · doi:10.1109/eaeeie50507.2021.9530874 · Cited by 5 · see citing works
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Hao, Y., Liu, Y., Liu, B., Amarantidis, G., & Ghannam, R. (2025) · IEEE Transactions on Education · doi:10.1109/te.2025.3536105 · Cited by 22 · see citing works
“Another driving factor is the importance of equipping students with the skills needed to fill the workforce gap [22], [23], [24], [29], [31], [34], [38], [39], [41], [43].”
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- Authors
- Cojocaru, D., Florin Manta, L., Abagiu, M., Dragomir, A., & Marin Mariniuc, A.
- Affiliations
- University of Craiova (RO)
- University of Craiova,Mechatronics and Robotics Departament,Craiova,Romania
- Venue
- 2022 31st Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE)
- Publisher
- IEEE
- Published
- 2022-06-29
- Pages
- 1-6
- OpenAlex
- W4285099877
- Cited by
- 1
- References
- 7
- Citations by year
- 2025: 1
- FWCI
- 0.82
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Mechatronics Education and Applications
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Robotics and Engineering
- Keywords
- deep learning in education, mobile robot control, casting defect detection, automotive engines, Jetson Nano, knowledge representation
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