Modeling and Control of Stiff Robots for Flexible Manufacturing

Abstract: To survive on a global market, small and medium size enterprises (SMEs) require affordable and competitive industrial automation for high quality flexible manufacturing. This thesis contributes to the development of robot concepts that fit the needs of SMEs. A major part of the thesis deals with the modeling of the three degree-of-freedom (DOF) Gantry-Tau parallel kinematic robot, which has the potential to fulfill the requirements on accuracy, mechanical stiffness and conceptual flexibility of a robot for SMEs. Additionally, concepts that aid the SMEs to achieve the required accuracy and a more intuitive robot operation were developed and evaluated. The modeling of the Gantry-Tau robot includes both kinematic and dynamic modeling. Based on the nominal kinematic model, kinematic error models were developed, as well as kinematics for the F1-type Gantry-Tau, a Gantry-Tau architecture extended to 6~DOF. The modeling was evaluated in kinematic calibration experiments. A rigid body model was derived and identified, including friction in the actuators. As noticeable flexible behaviour was observed, the compliance dynamics were identified by black box modeling. Kinematic calibration was not only considered for evaluation of the kinematic models developed, but it was also studied how to automize the kinematic calibration procedure, so that it can be executed by non-expert SME staff after a possible geometric reconfiguration of the robot. In the search of affordable, accurate and reusable measurement devices for kinematic calibration in SMEs, the usage of camera vision for kinematic calibration was evaluated. To make the programming of a robot trajectory fast and intuitive, lead-through programming was recently introduced. A new concept for lead-through programming in contact situations is proposed in this thesis, where two force sensors are used. While the first sensor is used for guiding the robot, the second force sensor measures the tool force, which can prevent damage of the tool or workpiece and can help to keep a steady contact between tool and surface. The concept was demonstrated in two example applications. A possibility to improve the performance for a repeatedly executed motion is iterative learning control (ILC). An ILC algorithm is evaluated on the Gantry-Tau robot, which uses an estimate of the tool motion, based on measurements from an accelerometer mounted at the end-effector plate and in addition to measurements on the motor side. The performance of the tool motion was shown to be considerably improved compared to the case when only motor side measurements are used.