Nemanja Kovincic
Papers
2
Total Citations
14
H-Index
2
About
Nemanja Kovincic is a leading researcher in the field of human-robot collaboration, with a focused expertise on ensuring safety in physical human-robot interaction. His major contributions center on developing predictive models and decision-making frameworks to assess and mitigate risks during unexpected contact events. Specifically, his work addresses the challenge of safe collaboration in quasi-static impact situations, where robots and humans may come into contact at low speeds. His most cited paper, "A Boosted Decision Tree Approach for a Safe Human-Robot Collaboration in Quasi-static Impact Situations" (2020, 9 citations), introduces a machine learning-based method to dynamically evaluate collision severity and trigger appropriate robot responses. In his earlier work, "A model‐based strategy for safety assessment of a robot arm interacting with humans" (2019, 5 citations), he established a validated dynamic simulation approach to determine contact forces, leveraging well-known parameter identification techniques for robot models. Kovincic’s research provides a critical bridge between theoretical safety standards and practical implementation, enabling robots to work more closely and safely alongside humans in manufacturing and service environments. His work is essential reading for engineers and researchers developing next-generation collaborative robotic systems.
Research Focus
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Top Papers
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