Scanning micromirrors have been used in a wide range of areas, but many of them do not have position sensing built in, which significantly limits their application space. This paper reports an integrated optoelectronic position sensor (iOE-PS) that can measure the linear displacement and tilting angle of electrothermal MEMS (Micro-electromechanical Systems) scanning mirrors. The iOE-PS integrates a laser diode and its driving circuits, a quadrant photo-detector (QPD) and its readout circuits, and a band-gap reference all on a single chip, and it has been fabricated in a standard 0.5 μm CMOS (Complementary Metal Oxide Semiconductor) process. The footprint of the iOE-PS chip is 5 mm × 5 mm. Each quadrant of the QPD has a photosensitive area of 500 µm × 500 µm and the spacing between adjacent quadrants is 500 μm. The iOE-PS chip is simply packaged underneath of an electrothermally-actuated MEMS mirror. Experimental results show that the iOE-PS has a linear response when the MEMS mirror plate moves vertically between 2.0 mm and 3.0 mm over the iOE-PS chip or scans from −5 to +5°. Such MEMS scanning mirrors integrated with the iOE-PS can greatly reduce the complexity and cost of the MEMS mirrors-enabled modules and systems.

Fourier transform spectrometers (FTS) based on piston-scanning MEMS mirrors have clear advantages of small size and low cost. However, the performance of this type of MEMS FTS is seriously limited by the difficulty of precisely controlling the tilt angle of the MEMS mirror plate during its piston scanning. This paper reports an integrated tilt angle sensing method, which is achieved via a mixed signal integrated optoelectronic position sensor (iOE-PS) that is bonded directly on the back of an electrothermally-actuated MEMS mirror. The iOE-PS integrates a laser diode, a band-gap reference, a quadrant photo-detector (QPDs), and the QPDs' readout circuits all on a single chip. The iOE-PS has been fabricated in a 180 nm CMOS process. Experimental results show that the iOE-PS has a linear response when the MEMS mirror plate moves vertically between 1.31 mm to 1.50 mm over the iOE-PS chip; the tilt angle can be measured up to at least 5° with a resolution of 0.0067°. The iOE-PS can greatly reduce the size and complexity of MEMS mirrors-enabled systems with integrated closed-loop control capability.

Supervoxels have a widespread application of instance segmentation on account of the merit of providing a highly approximate representation with fewer data. However, low accuracy, mainly caused by point cloud adhesion in the localization of industrial robots, is a crucial issue. An improved bottom-up clustering method based on supervoxels was proposed for better accuracy. Firstly, point cloud data were preprocessed to eliminate the noise points and background. Then, improved supervoxel over-segmentation with moving least squares (MLS) surface fitting was employed to segment the point clouds of workpieces into supervoxel clusters. Every supervoxel cluster can be refined by MLS surface fitting, which reduces the occurrence that over-segmentation divides the point clouds of two objects into a patch. Additionally, an adaptive merging algorithm based on fusion features and convexity judgment was proposed to accomplish the clustering of the individual workpiece. An experimental platform was set up to verify the proposed method. The experimental results showed that the recognition accuracy and the recognition rate in three different kinds of workpieces were all over 0.980 and 0.935, respectively. Combined with the sample consensus initial alignment (SAC-IA) coarse registration and iterative closest point (ICP) fine registration, the coarse-to-fine strategy was adopted to obtain the location of the segmented workpieces in the experiments. The experimental results demonstrate that the proposed clustering algorithm can accomplish the localization of industrial robots with higher accuracy and lower registration time.

Electrohydrodynamic (EHD) printing is a promising micro-nano manufacturing technology. However, the EHD printing process is susceptible to interferences like charge repulsion, electric field, airflow, and platform motion, leading to unstable jetting and nonuniform deposition morphology. In this paper, a double close-loop fuzzy control method based on jet image recognition and micro-current measurement was designed to monitor and control the EHD printing process. A closed-loop control based on the fuzzy control algorithm has been designed to monitor the EHD printing system by taking the feedback information from micro-current and jet image. The experimental results show that the closed-loop control significantly improved the uniformity and stability of the fiber deposition. The volatility percentage of the current decreased from 34% to 12%, the fluctuation range of the fiber diameter was reduced from 35 μm to 15 μm, and the volatility percentage of the fiber spacing decreased from 29% to 9.5%. Additionally, the closed-loop control accelerated the response speed of jet mode conversion. Ineffective deposition of printing jet on the collection plate was shortened from 5 s to 2.2 s. This feedback control optimises the printing quality of micro-nano structures, promoting the advancement of high-resolution additive manufacturing applications.

Micro-electro-mechanical system (MEMS) scanning micromirrors are playing an increasingly important role in active structured light systems. However, the initial phase error of the structured light generated by a scanning micromirror seriously affects the accuracy of the corresponding system. This paper reports an optoelectronic integrated sensor with high irradiance responsivity and high linearity that can be used to correct the phase error of the micromirror. The optoelectronic integrated sensor consists of a large-area photodetector (PD) and a receiving circuit, including a post amplifier, an operational amplifier, a bandgap reference, and a reference current circuit. The optoelectronic sensor chip is fabricated in a 180 nm CMOS process. Experimental results show that with a 5 V power supply, the optoelectronic sensor has an irradiance responsivity of 100 mV/(μW/cm²) and a −3 dB bandwidth of 2 kHz. The minimal detectable light power is about 19.4 nW, which satisfies the requirements of many active structured light systems. Through testing, the application of the chip effectively reduces the phase error of the micromirror to 2.5%.

Scanning micromirrors represent a crucial component in micro-opto-electro-mechanical systems (MOEMS), with a broad range of applications across diverse fields. However, in practical applications, several factors inherent to the fabrication process and the surrounding usage environment exert a considerable influence on the accuracy of measurements obtained with the micromirror. Therefore, it is essential to calibrate the scanning micromirror and its measurement system. This paper presents a novel scanning micromirror calibration method based on the prediction of a particle swarm optimization-least squares support vector machine (PSO-LSSVM). The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. The decision factor ($R^2$) for this model at the x-axis reaches a value of 0.9947.