Accuracy Quantification and Improvement of Serial Micropositioning Robots for In-Plane Motions

High positioning accuracy with micropositioning robots (MPRs) is required to successfully perform many complex tasks, such as microassembly, manipulation, and characterization of biological tissues and minimally invasive inspection and surgery. Despite the widespread use of high-resolution micro-and nanopositioning robots, there is very little knowledge about the real positioning accuracy that can be obtained and what the main influential factors are. Indeed, very few notable methods are available to measure multi-degree-of-freedom motions with adapted range, resolution, and dynamic capabilities. The main objective of this paper is to quantify the positioning accuracy of serial MPRs and to identify the main influential factors (a typical XY Theta serial robot is chosen as a case study). To reach this goal, a measuring system that combines vision and pseudoperiodic patterns with an extremely large range-to-resolution ratio is introduced as a new way to quantify the positioning accuracy of MPRs for in-plane motions. Then, an open-loop control approach based on MPR calibration is chosen for several reasons: the use of different models to identify influential factors, the quantification of the positioning accuracy, and the necessity of the method when sensor integration is too complex. Experiments using five different calibration models were conducted to classify factors influencing the positioning accuracy of MPRs. The results show that positioning accuracy can be improved by more than 35 times from 96 mu m with no imperfection compensation to 2.5 mu m by compensating for geometric, position-dependent, and angle-dependent errors through the MPR calibration approach.