Milling strategies optimized for industrial robots to machine hard materials

Industrial robots offer a good basis for machining from a conceptual point of view. Still they are rarely utilized for machining applications in industry compared to CNC machines due to their low stiffness and the bad achievable work piece quality. Available compensation approaches, like online compensation approaches to increase position accuracy using costly additional hardware and measurement equipment as well as offline compensation approaches using a set of empirical measurement data and models to predict deviation, try to compensate errors whether to already avoid them if possible. In this paper milling and robot strategies are proposed to increase work piece quality without additional hardware or models. Experimental validations of the results have been performed for different kinds of shapes and materials.