Angelina Iakovets

About

Angelina Iakovets is a leading researcher at the intersection of intelligent manufacturing, collaborative robotics, and human–robot interaction. Her work is central to the Industry 4.0 paradigm, where she pioneers the integration of mixed reality, collaborative robots (cobots), and AI-driven assistance systems to revolutionize assembly processes. Her most cited paper (28 citations) introduces an experimental work cell for assisted assembly of customized products using 3D virtual models and CNN training, demonstrating a practical framework for flexible automation. She further advances the field with her 2025 study on intelligent human–robot interaction assistants, addressing the critical need for adaptive cobot systems in dynamic environments—a market projected to capture 33% of industrial robotics by 2030. Iakovets also contributes to predictive maintenance and soft robotics, developing optimization frameworks for continuum robot control. Her decision-making model for engineering education reflects a commitment to training the next generation of engineers. With a growing citation impact and a portfolio spanning from real-time data collection to soft actuator optimization, Iakovets is shaping the future of smart, human-centric manufacturing.

Research Focus

Key Achievements

Top Papers

1. 1
   CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots

   28 citations · 2021
2. 2
   Intelligent Human–Robot Interaction Assistant for Collaborative Robots

   4 citations · 2025
3. 3
   Design of a Decision-Making Model for Engineering Education

   2 citations · 2024
4. 4
   Predictive Maintenance of Industrial Robots Based on Real-Time Data Collection

   1 citations · 2025
5. 5
   Optimization of Soft Actuator Control in a Continuum Robot

   1 citations · 2025

Key Collaborators

Contact & Links