Compensation of kinematic transmission errors on industrial robots (HyComp II)

• Applicant: Professor Dr.-Ing. Alexander Verl
• Subject Area: Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 443677015

Industrial robots (IR) offer significant advantages over conventional machine tools in terms of a larger work space, higher flexibility and lower investment cost. However, the lower path accuracy of IR compared to conventional machine tools limits their application possibilities. Especially for machining tasks, where the path accuracy is a decisive factor for the quality of the manufacturing process, the accuracy of IR is inferior to conventional machine tools by a factor of 100 to 1000. This circumstance prevents the widespread use of IR for many machining processes. The reasons for the occurring path errors are to be attributed in particular to the nonlinear dynamics of the robot joints or their drive train. These are in turn caused by the employed precision transmissions and their transmission errors resulting from hysteresis as well as kinematic transmission errors. In the first funding period, the multidimensionality (load, temperature, frequency) of the hysteresis and friction behavior of robot transmissions was investigated and modeled. Based on this, a method was developed to compensate for the torsion caused by hysteresis. On a single-axis test bench, it was demonstrated that this reduces the tracking error by up to 90 % with respect to the motor-based P-PI control without compensation. The remaining error portion is largely due to the kinematic transmission errors of the transmissions. However, these are still too large for advanced machining tasks. The main focus of the second funding period is the investigation and modeling of the multidimensionality of the kinematic transmission errors as well as their compensation. This should qualify IR without additional sensors to perform demanding machining tasks.

• DFG Programme: Research Grants
• Co-Investigator: Dr.-Ing. Armin Lechler