Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

Abstract

Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV) of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

Effect of alignment angle on the alignment accuracy of a miniature rotation robot for microscopy imaging

“…The nanopositioner's movement mechanism is slip-stick mechanism. 24 The details of the rotation robot's shape, structure, technical specifications, and other parameters can be found in the study by Shen et al 23 The rotation robot would rotate so that samples can be observed from different directions. However, when samples are not on the rotation axis of the miniature robot, samples Figure 1, the relative position between samples and rotation axis is calculated based on sample's position shift on microscope images during miniature robot and sample's rotation.…”

“…The relative position between samples and rotation axis would be calculated based on those three coordinates. 23 Suppose that a point on the sample has coordinate ðx N ; y N ; z N Þ in fNg and the same point has the coordinate ðx M ; y M ; z M Þ in fMg, then the following equation can be achieved 25 x M y M z M …”

“…Although the alignment angle-based alignment has been realized in the study by Shen et al, 23 the reference doesn't analyze factors that affect the alignment accuracy of the miniature rotatable robot. Thus, this work is proposed to examine the effect of alignment angle on alignment accuracy through both theory analysis and experiments.…”

“…Most recently, a rotatable robot has been integrated with optical microscope and SEM to capture images for samples from multidirection. 23 The authors then adapt imaging processing technique to get a panorama image and dome projection result based on those captured images from various directions. Shen et al 23 introduced the basic principal of the alignment, which is to align samples to robot's rotation axis to prevent samples from moving out of microscope's FOV.…”

“…23 The authors then adapt imaging processing technique to get a panorama image and dome projection result based on those captured images from various directions. Shen et al 23 introduced the basic principal of the alignment, which is to align samples to robot's rotation axis to prevent samples from moving out of microscope's FOV. In the alignment, the sample is rotated forward and backward by an alignment angle.…”