My research is deeply rooted in Robotics and Automation. Initially, I focused on computer vision and object detection, later expanding into machine learning techniques and filtering methods for self-localization, tracking, and state estimation in robotics. More recently, my work has shifted towards multi-robot coordination, navigation, and planning for autonomous systems operating in industrial and natural environments, including human-inhabited and agricultural settings. Additionally, I specialize in simulating these complex systems through digital twinning, which plays a crucial role in training logic-, rule-, and AI-based approaches.