Self-calibration of a class of parallel manipulators

A general numerical method is introduced in this paper for the self-calibration of parallel manipulators. The concept of creating inverse measurement residuals by exploring conflicting information provided with redundant sensing is generalized. A numerical kinematic analysis method is adopted to systematically compute the inverse measurement residuals. By this treatment, the design of a suitable self-calibration system became more systematic, and existing kinematic parameter estimation techniques can be applied for the self-calibration of parallel mechanisms. It is shown that by installing 2 or more redundant sensors on the Stewart platform, the system is able to perform self-calibration. It is possible to calibrate part of the system using a reduced number of redundant sensors; the identification algorithm converges rapidly; its accuracy performance is satisfactory; and the extension of the method to other parallel manipulators is straightforward.