Automating Robotic Micro-Assembly of Fluidic Chips and Single Fiber Compression Tests Based-on Θ Visual Measurement With High-Precision Fiducial Markers

At small scales, automating robotic tasks such as assembly, force/displacement characterization, positioning, etc., appear to be particularly limited. This is due to the lack of sufficiently performing and easy-to-implement multi-degrees-of-freedom measurement systems able to measure the relative pose between micro-parts. In order to address this issue, a measurement method based on High-Precision fiducial markers (named HP code) is proposed. This measurement method combines a periodic pattern (providing high resolution by phase-based computation) with more regular QR codes (bringing versatile implementations and a quick detection). The design and method to efficiently locate these HP codes are presented in this paper. Experimental investigations demonstrate ultra-high resolution: 2 nm and 5 ~\mu rad along X,Y and \Theta respectively (i.e. one thousandth of a pixel typically). The method is designed to be scalable as well as self-calibrated and to provide high robustness and high versatility. Two typical challenging applications in the field of microrobotics are automated to demonstrate these disruptive performances and the easy-to-implement capability of the method: (1) the automated assembly of two micro-fluidic chips through visual servoing with an achieved positioning accuracy below 50 nm, and (2) the automated micromechanical characterization of single fibers achieved by the integration of HP codes into a compliant structure enabling simultaneous micro-force and displacement sensing capabilities. These achievements highlight the versatility of the method and open the door to the rapid automation of high-quality robotic tasks at the micro scale. Note to Practitioners-The motivation for this work/study is based on the fact that many application areas are extensively orienting towards microrobotic systems to perform precise tasks with versatility. However, at the micro scale, many disturbances such as the effects of climate change strongly affect this precision. This problem is amplified by the fact that sensors cannot be easily integrated, either by lack of space or by the lack of measurement systems available. Vision-based approaches are widespread at this scale and appear very promising to measure the relative pose between micro-parts. N