Human movement depends on complex interactions between the brain, nervous system, muscles, and body. The brain does not calculate the exact force required for every muscle and joint; instead, the body\u2019s mechanical properties and neural reflexes help coordinate movement automatically.<\/p>\n\n\n\n
Led by Daniel H\u00e4ufle, Georg Martius, and Pierre Schumacher, this project investigated whether morphological computation<\/strong> could help AI systems learn human-like movement more efficiently. Morphological computation refers to the way the body itself contributes to movement through its structure, materials, and passive mechanical responses.<\/p>\n\n\n\n The project was carried out at the University of T\u00fcbingen between 2021 and 2024.<\/p>\n\n\n\n The project shows how the physical structure of a body can contribute to intelligent movement and reduce the burden on a control system. This could help researchers build robots that move more efficiently, adapt more naturally to disturbances, and interact more safely with their surroundings. The findings may support future applications in healthcare, rehabilitation, prosthetics, and advanced manufacturing.<\/p>\n\n\n\nKey results<\/h2>\n\n\n\n
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Why it matters<\/h2>\n\n\n\n
This project produced the following peer-reviewed publications: <\/h2>\n\n\n\n
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