Speakers > Tamim Asfour

Tamim Asfour

Tamim Asfour

Professor, Karlsruhe Institue of Technology

Title: Robotics AI: Cognitive Abilities for Intelligent Bodies

Summary: Engineering robots with human like-abilities in the real world remains a grand challenge. Currently, we experience AI systems with superhuman performance in image and speech processing, medical diagnosis and games. However, the underlying techniques of these systems do not allow the transferability of solutions to different context in the same domain let alone across different domains. In robotics, motion is fundamental! The development of motion abilities requires the integration of perception and action while taking into account the physical body - the bodyware – and the interaction with the real world leading to transferable cognitive abilities. This is where current AI technologies fail. Robotics AI emphasizes the interaction between cognitive abilities and intelligent bodies to create robots with human-like abilities and even superhuman performance. I will discuss current progress (and limitations) of current AI and robotics and describe our efforts towards building humanoid robots with motion intelligence.

Bio: Tamim Asfour is full Professor of Humanoid Robotics at the Institute for Anthropomatics at KIT. His research focuses on the engineering of high performance 24/7 humanoid robotics as well as on the mechano-informatics of humanoids as the synergetic integration of mechatronics, informatics and artificial intelligence methods into humanoid robot systems, which are able to predict, act and interact in the real world. Tamim is the developer of the ARMAR humanoid robot family. He is the Founding Editor-in-Chief of the IEEE-RAS Humanoids Conference Editorial Board, president of the Executive Board of the German Robotics Society (DGR) and scientific spokesperson of the KIT Center “Information · Systems · Technologies (KCIST)”. In his research, he is reaching out and connecting to neighboring areas in large-scale national and European interdisciplinary projects in the area of robotics in combination with machine learning and computer vision.

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