Nowadays a lot of effort is put into trying to reproduce human behavior. Thus, neuroscience know-how can be leveraged to create a variety of robotic applications in which neural substrates of motor skill learning are transferred to artificial machines in terms of perception and dexterity. An important benchmark for testing analogies and differences in learning techniques can be presented through a game. In this project, control systems are investigated to allow a robotic arm to play Jenga. In particular, this master’s thesis aims at comparing motion control in Operational Space and Visual Servoing control techniques. Therefore, keywords are path planning, force interaction, mechanical design and sensor fusion.