Optimal Calibration of Parallel Kinematic Machines

Abstract

In this paper, a new method for optimal calibration of parallel kinematic machines (PKMs) is presented. The basis of the methodology is to exploit the least error sensitive regions in the workspace to yield optimal calibration. To do so, an error model is developed that takes into consideration all the geometric errors due to imprecision in manufacturing and assembly. Based on this error model, it is shown that the error mapping from the geometric errors to the pose error of the PKM depends on the Jacobian inverse. The Jacobian inverse would introduce spurious errors that would affect the calibration results, if used without proper care. Hence, areas in the workspace with smaller condition numbers are selected for calibration. Simulations and experiments are presented to show the effectiveness of the proposed method. Calibration software based on the proposed method has been embedded in the tripod developed at the National Research Council of Canada’s Integrated Manufacturing Technologies Institute.