Precise Watch-Hand Alignment Under Disturbance Condition by Microrobotic System

Abstract

Accurate alignment of the watch hand is a critical procedure in the industrial production of watches. However, compared with the traditional ideal laboratorial case, the watch-hand alignment suffers various external disturbances from the aged equipment and industrial operating conditions, which seriously influence the alignment precision. To achieve accurate watch-hand alignment in the complex industrial environment, this paper develops a robotic micromanipulation system and proposes a corresponding robust control strategy. First, a micromanipulation system with five degrees of freedom is set up and integrated with an optical microscope. Then, a set of proper machine vision methods is adopted to obtain accurate position information in disregard of the interference terms. Third, the dynamic model of the controlled watch hand is built with consideration of the external disturbances from the production environment. Since the velocity information cannot be observed accurately through the machine vision process, we design a state observer to acquire the position and velocity values for the following control strategy. After that, a sliding mode controller with the radical basis function neural network is proposed to achieve high-precision alignment while resisting the external disturbance. Finally, simulation and experimental results prove that the proposed method can realize the alignment of the watch hand within 6 s with the accuracy of $2\times 10^{-3}$ rad, which is enhanced at least two times compared with the traditional manual method. Note to Practitioners —This paper was motivated by the challenging problem of the watch-hand alignment in the industrial production. Unlike the traditional manipulation, this alignment is subjected to various disturbances from the aged equipment and complex operating conditions, including complex forces at the air–liquid operation interface and the confusing scratches, undesired flaking particles, as well as the reflection of light in the image. Here, we propose a microrobotic system and a robust control strategy to precisely align the watch hand and eliminate the influence from the above disturbances. In the machine vision process for recognizing the object, filtering, contour/corner detection, and template matching methods are adopted to acquire accurate position information despite the interference in image processing. To avoid the disturbance from the complex forces during the alignment, we develop the robust sliding mode controller to guarantee the alignment precision. The experiment results indicate that the proposed system can align the watch hand with the accuracy enhanced at least two times as previous manual method. This paper provides a general solution for micromanipulation under disturbance in industrial production environment.