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Foto: Andreas Heddergott/TU Muenchen
Research Priorities: Robotics, embodied AI (embodied artificial intelligence), collective intelligence, human-robot interaction, motor intelligence
Sami Haddadin is an electrical engineer and computer scientist who conducts research in the fields of robotics, artificial intelligence and human motor control.
A strong interdisciplinary focus of his work – in addition to the development of a wide variety of intelligent machines – lies in the interface between the development of intelligent machines and the basic principles of the human body and its functionality. Their understanding is key to the development of autonomously interacting machines that will support humans in the future in key areas such as work, health, mobility, the environment, or space.
In addition to exploring the fundamentals of robotics and artificial intelligence, the overarching goal of Sami Haddadin's research group is to make state-of-the-art robotics accessible to laypeople for the first time utilizing intelligent programming, learning and interaction systems that interactively link humans and machines. Commercial introduction of this technology can thus represent a change towards intelligent machines meeting people's needs more broadly, beyond industrial use. Examples can be found in healthcare in assisting the sick, elderly or disabled. The concept developed by Sami Haddadin and other researchers for cost-effective, flexible and intuitively operable robots turns them into aids for humans.
From Sami Haddadin's point of view, there are still some significant challenges ahead before robotics, and artificial intelligence can be merged into machine intelligence: For one, the technological boundaries of sensorimotor and integrated system design must be significantly expanded in order to get closer to the unique performance and embodied intelligence of the human body. Secondly, the two previously separate paradigms of model-based control and regulation and data-driven machine learning algorithms must be united in such a way that the next generation of AI algorithms seamlessly bridges the gap between the physical and virtual worlds.