Robotics
Our research explores how AI can enhance robotics by addressing inverse and control problems, enabling robots to perceive and act reliably in uncertain environments. Beyond control, we develop methods for recognition, manipulation, and prediction that support flexible interaction with objects and adaptation to dynamic scenarios. By combining mathematical theory and machine learning, we aim to create stable, interpretable, and trustworthy AI tools that open new possibilities in manufacturing, healthcare, and human–robot collaboration.
