LAUSR

This article proposes an original approach for robotic calibration that is based on measurements along a single direction (1-D). Among all applications, the field of microrobotics and nanorobotics has been chosen as case study because of the strong needs for high positioning accuracy (10–100 nm typically) while measuring with sufficient resolution along multi-degrees of freedom (DoF) is still a fully open question. The 1-D measurements relying on Fabry–Perot (FP) interferences is used, and the proposed modeling of a 6-DoF nanopositioning robot enables to derive the measurement strategy as well as the identification procedure for both extrinsic and intrinsic parameters. Experimental investigations demonstrate that the approach is easy to implement, low cost, and enables to understand what are the main influential parameters onto positioning accuracy. They also conduct to very high accuracy in 6-DoF positioning; a positioning accuracy estimate of 50 nm and 0.004° has notably been obtained for the full pose (position and orientation, respectively) and can be held during several hours after the measurements. Note to Practitioners—The motivation of this work is to give an answer to the growing needs for micro nanopositioning robots having a very high precision for applications in microassembly, in the characterization of micro and nano components or biological elements, or for minimally invasive surgery. The key contribution of the proposed work relies on the method proposed that enables to efficiently calibrate a serial 6-degree-of-freedom (DoF) robot using only 1-D interferometric measurements, which overcomes the need for multi-DoF, small size, and high-resolution sensors missing in commercial offers. Moreover, the behavior of such novel robotic solutions is not well known, difficult to model, and there is a clear lack of knowledge about the main influential parameters. The method proposed in this article notably enables to achieve the full calibration of the robot (all intrinsic and extrinsic parameters identified) to reach the best positioning accuracy. This first part takes times, and this article shows that it is then possible to adopt a less time taking procedure by only reidentifying extrinsic parameters and thus to hold these performances over long periods, typically a week.