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Deep

Agency

                     Master Thesis  

                                                                           Stuttgart University

                                                 Year: 2023

Collab with S.Sardari and P.Zhang

 

Industry 5.0 aims to reintegrate humans into the workforce alongside robots, but current industrial robots lack the dexterity and high autonomy needed for collaboration with human workers in construction. To facilitate better human robot collaboration, there is a need for more intuitive robot programming that allows skilled workers to program robots with ease. This research aims to combine the fields of human-robot collaboration, robotic timber assembly, and machine learning to develop a system that transfers human skills to robots through haptic robot training. By combining deep reinforcement learning with haptic teaching from human instructors can equip robots with enhanced autonomy and adaptability to their surroundings, thereby liberating human workers to focus on tasks that require human intelligence for decision-making. 


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