Combined offline simulation and online adaptation approach for the accuracy improvement of milling robots

Industrial robots, used for milling processes, have to execute highly dynamic and accurate movements. External static and dynamic process forces lead to static deflections and dynamic excitations. In this paper, we present a coupled offline simulation and planning strategy of the machine-process interaction with online adaptation mechanisms for increased system robustness. The process planning, optimization and milling force prediction are executed offline, while the online compensation and adaptation accounts for static deflections and unmodeled disturbances. The benefits of the combined offline and online approach are demonstrated by stabilizing machining processes and accurate deflection compensation with unmodeled changes in spindle speed and feed rate for the machining of aluminum workpieces.