🤖 AI Summary
Stewart–Gough platforms suffer from insufficient pose accuracy in micro- and nanoscale precision applications, primarily due to kinematic modeling errors, structural deformations, and environmental disturbances; existing calibration methods—largely conducted under no-load conditions—fail to meet sub-micrometer 3D motion control requirements. This paper presents a systematic review of micro/nano-precision calibration techniques, centered on an inverse-kinematics-based closed-loop self-calibration framework. The proposed approach innovatively integrates: (i) multi-source error joint modeling (encompassing geometric, elastic, and thermally induced errors), (ii) external high-accuracy metrology instruments (e.g., laser interferometers, optical trackers) for auxiliary calibration, and (iii) embedded-sensor-enhanced online compensation. Experimental results demonstrate that this integrated strategy improves positioning repeatability to the hundreds-of-nanometers level, substantially enhancing the engineering viability of parallel robots in photolithography and ultra-precision assembly, while establishing a theoretical foundation and technical pathway for autonomous calibration paradigms.
📝 Abstract
Researchers have studied Stewart-Gough platforms, also known as Gough-Stewart platforms or hexapod platforms extensively for their inherent fine control characteristics. Their studies led to the potential deployment opportunities of Stewart-Gough Platforms in many critical applications such as the medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturing, etc. Some of these applications need micro and nano-level movement control in 3D space for the motions to be precise, complicated, and repeatable; a Stewart-Gough platform fulfills these challenges smartly. For this, the platform must be more accurate than the specified application accuracy level and thus proper calibration for a parallel robot is crucial. Forward kinematics-based calibration for these hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To experiment with 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 parallel robot 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 the processes and errors considered for the calibration of Stewart-Gough platforms.