Abstract
Robot machining processes with high material removal rates lack of high path accuracy mainly due to the low stiffness of industrial robots. The low stiffness leads to process forces caused deviations of the tool center point (TCP) from the planned position of more than 1 mm in industrial applications. To enhance the path accuracy a novel hybrid compliance compensation is developed. It combines a force sensor and model based online compensation with forces of an offline simulation to instantly react to predictable high force changes e.g. at a milling cutter exit from the work piece. The method is applied to a KUKA KR 300 robot. A compliance model based on a forward kinematic with virtual joints is implemented on an external controller. Cartesian or axis specific compensation values are calculated and transferred to the robot via a control circuit. A compliance measurement method is developed and a force torque sensor is mounted to the flange of the robot. The system is validated in with Cartesian and axis specific compensation values as well as with and without pilot control.
Highlights
Introduction and state of the artFor decades, industrial robots have been an integral and steadily growing part of industrial production chains
The negative effects of milling cutter exits on compensation quality can be significantly reduced
The stiffness values of a KUKA KR 300 robot are identified with a developed measurement system and the compliance compensation method is applied to the robot
Summary
Industrial robots have been an integral and steadily growing part of industrial production chains. In addition to tasks in the fields of material handling and welding, applications that require high robot accuracy, in the range of a few tenths of a mm, are becoming established These include tasks in the area of quality assurance, as well as machining of large components. Process force models are coupled with multi-body-models of robots to predict compliance [3, 14, 16] or backlash [5] caused path deviations and compensate or reduce them. They can be combined with model-based workpiece placing and process parameter optimization [18]. The combination of path planning and process parallel methods represent a promising, but so far not validated, approach [11] to avoid significant differences between predicted and actual machining forces as well as high reaction times of the robot
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