Robot Tool Calibration of an Active Pen with Python using an Enabled Surface from Anoto Technology

Abstract: This master thesis has shown multiple uses of the Anoto dot pattern and Anoto pen for different applications. One application is the calibration of the robot tool and work object. Another is the use of an Anoto pen and paper as replacement of the ABB Flexpendant to create a lightweight and intuitive control device to control an industrial robot, experimentally demonstrated for the IRB140 robot arm. The Python programming language and interpreter were used together with ABB’s RAPID programming language to create a framework to handle the communication between the user and the robot. The inverse and forward kinematics were derived for the robot and used for simulations and for determining if a trajectory could be traversed. This helped in the theoretical verification in the development of the calibration algorithm. The calibration details from the results section show that a naive approach to calibrating the tool tip, i.e., using all of the measurement values results in a deviation of 1mm or more with slow convergence compared to the manual calibration of 0.5mm deviation. By using a greedy optimization strategy of successively adding measurements that improve the calibration, and removing measurements that worsen it, we get a calibration comparable to a manual calibration with fast convergence. The work object calibration, i.e., the orientation estimation of the Anoto pattern surface shows promising results with few measurements and faster convergence, but can also be improved with the same optimization strategy. By performing manual measurements, and using measurements of the error in the robot flange position, a realistic lower bound on the precision of the calibration algorithm was decided to be no lower than 0.3 - 0.4mm, and depended on the performance of the pen. The flexpendant control board replacement was developed through a user study with volunteers from Anoto.