Viktor Rjabtšikov

The challenge in modern industry is to find the best ways for human-robot interaction in workplaces, enabling robots to realize optimal solutions by combining AI and human capabilities. The project's goal is to contribute to the automation of company production processes, focusing on the social and psychological aspects of human-robot collaboration to ensure that human workers in the industry feel safe and satisfied. Research directions include: - creating a collaborative robotics experimental lab - designing robotized workplaces - modelling of human-robot interaction, assessments and analysis of influencing factors and risks. Expected results are methodologies and validated human-robot interaction models, skills for their implementation, impact factors and risk assessments, a developed laboratory with hardware, software and expertise; providing user-centred design solutions services. All of this leads to safer human-robot interactions, increasing user trust in robotic systems.

The objective of the EEV5040 Industrial Automation and Drives activity is to introduce students to the importance of industrial automation and electric drives and the latest trends in these fields (including IoT). As a result of the development activities, students will acquire in-depth knowledge of electric drive management, model-based design methodology and IoT applications in industrial automation in the future. They are able to create, adapt and analyse electric motor control systems and solve real problems in this field. These results influence the quality of industry-specific ICT teaching, providing students with the practical skills and knowledge essential to today's industrial automation. Within the framework of the development project, the subject EEM0040 Machine vision is also amended, where the traditional machine vision curriculum is added to it by adding the hyperspectral technology component. The aim of the development activity is to combine concepts of machine vision with hyperspectral data processing. Within the subject, students will develop practical skills in the use of hyperspectral cameras, from camera setup to processing of various hyperspectral images. They acquire knowledge of the specifics of hyperspectral data, such as the wavelength spectrum and its relationship to the properties of materials. In addition, they learn the methods of machine vision, which allow to identify different objects and characteristics from hyperspectral images.

This project is a side project of the superior research project that has been supported by the Estonian Research Council under grant PSG453, "Digital twin for propulsion drive of an autonomous electric vehicle". It is conducted by the TalTech Mechatronics and Autonomous Systems Research Group. So far, the vehicle's drive but not the wheels' properties have been considered for the development of the digital twin. The task of this sub-project is the development of a test bench for wheels with the associated simulation. The influence of the different properties of wheels on the entire vehicle should be simulated as realistically as possible. Additionally, this project includes knowledge exchange and laboratory visits both in Germany and Estonia. The aim is to popularize knowledge among young people, introducing digital twins to aspiring engineers.