In this paper, a robotic arm moving along a user-defined trajectory is used to calibrate a short-range magnetic positioning system (MPS). Such system estimates the position and attitude of an active transmitting coil by measuring the induced voltage on a set of fixed receiving coils, with known position and orientation. This estimate is obtained by solving an optimization problem that can be decomposed into a linear and a reduced nonlinear problem. Then, a Kalman Filter is used to process the estimated positions and obtain smooth trajectories. Data acquisition and processing are performed in real time by the MPS. In this context, the robotic arm is used to provide ground truth, i.e., to move the active coil along a known trajectory, while simultaneously the MPS estimates the position of the active coil. Such ground-truth information is then used to calibrate the MPS and improve its accuracy. To align the robotic arm with the MPS, a preliminary calibration procedure of the robot is performed. Then, a wide ground-truth trajectory is used to estimate the calibration parameters of the MPS itself, namely, the positions and orientation of the fixed coils. To validate the efficiency of the calibration procedure, the accuracy of the MPS is evaluated across several trajectories. The results show that the mean positioning error is less than 3 mm. Finally, an on-the-fly calibration method simultaneously estimating positions and attitudes of both the active coil and all the receivers is investigated.