Martinš Sarkans

The central problem of the research topic is that there is no comprehensive methodology and technological systemic approach that would allow companies to assess the feasibility of digitalization and robotization of production systems before making investments and to propose needs-based solutions for automated workplaces, taking into account the actual functioning of production processes and the impact of various technological solutions on the entire production system. The aim of the research topic is to develop and validate an artificial intelligence-based decision support system and methodological framework that allows industrial companies to analyze production processes, model a virtual factory, create a digital twin of it, and assess the performance, profitability, and implementation capability of various automation solutions (including robotized workplaces, digital devices, and integrated work operations) in the company's production system before making physical investments.

Customization requirements in modern manufacturing demand a closer collaboration between operators and automated technologies, leading to a novel Human-Robot Collaboration (HRC) and interaction (HRI) paradigm aimed at augmenting human capabilities in the workplace. Digital Twin (DT) and Immersive technologies (XR) support the inclusion of the human operator in simulation-based interfaces intended for safe, efficient, multimodal, and adaptive HRI. The design and implementation of these interfaces are not yet adequately addressed. This project aims to define what is the current approach to the requirement definition for DT and XR by analyzing the potentials and challenges of the adoption of DT interfaces and other types of input methods in the HRC context, their allocation in the Human-Computer Interaction (HCI), and the state of current experimental research in this field as bringing the human back to the loop bring us the Industry 5.0 concept within industrial and healthcare domains.