A LITERATURE REVIEW ON STEWART-GOUGH PLATFORM CALIBRATIONS

Abstract

Researchers have studied Stewart platform-based Parallel Kinematic Machines (PKM) extensively for their fine control capabilities, for many applications including medicine, precision engineering machines, aerospace research, electronic chip manufacturing, automobile manufacturing, etc. These applications need micro and nano-level movement control in 3D space for the motions to be precise, complicated, and repeatable; a Stewart platform fulfills these challenges smartly. For this, the PKM must be more accurate than the specified application accuracy level and thus proper calibration for a PKM robot is crucial. Forward kinematics-based calibration for such hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To experiment different calibration techniques, various calibration approaches were implemented by using external instruments, constraining one or more motions of the system, and using extra sensors for auto or self-calibration. This survey paid attention to those key methodologies, their outcome, and important details related to inverse kinematic-based PKM calibrations. It was observed during this study that the researchers focused on improving the accuracy of the platform position and orientation considering the errors contributed by one source or multiple sources. The error sources considered are mainly kinematic and structural, in some cases, environmental factors also are reviewed, however, those calibrations are done under no-load conditions. This study aims to review the present state of the art in this field and highlight on the processes and errors considered for the calibration of Stewart platforms.