A Predictive Model of Capillary Forces and Contact Diameters between Two Plates Based on Artificial Neural Network

Many efforts have been devoted to the forecasting of the capillary force generated by capillary adsorption between solids, which is fundamental and essential in the fields of micro-object manipulation and particle wetting. In this paper, an artificial neural network (ANN) model optimized by a genetic algorithm (GA-ANN) was proposed to predict the capillary force and contact diameter of the liquid bridge between two plates. The mean square error (MSE) and correlation coefficient (R²) were employed to evaluate the prediction accuracy of the GA-ANN model, theoretical solution method of the Young-Laplace equation and simulation approach based on the minimum energy method. The results showed that the values of MSE of capillary force and contact diameter using GA-ANN were 10.3 and 0.0001, respectively. The values of R² were 0.9989 and 0.9977 for capillary force and contact diameter in regression analysis, respectively, demonstrating the accuracy of the proposed predictive model. The sensitivity analysis was conducted to investigate the influence of input parameters, including liquid volume and separation distance, on the capillary force and contact diameter. The liquid volume and separation distance played dominant roles in affecting the capillary force and contact diameter.

Precise Position Control of Holonomic Inchworm Robot Using Four Optical Encoders

In this study, an XYθ position sensor is designed/proposed to realize the precise control of the XYθ position of a holonomic inchworm robot in the centimeter to submicrometer range using four optical encoders. The sensor was designed to be sufficiently compact for mounting on a centimeter-sized robot for closed-loop control. To simultaneously measure the XYθ displacements, we designed an integrated two-degrees-of-freedom scale for the four encoders. We also derived a calibration equation to decrease the crosstalk errors among the XYθ axes. To investigate the feasibility of this approach, we placed the scale as a measurement target for a holonomic robot. We demonstrated closed-loop sequence control of a star-shaped trajectory for multiple-step motion in the centimeter to micrometer range. We also demonstrated simultaneous three-axis proportional-integral-derivative control for one-step motion in the micrometer to sub-micrometer range. The close-up trajectories were examined to determine the detailed behavior with sub-micrometer and sub-millidegree resolutions in the MHz measurement cycle. This study is an important step toward wide-range flexible control of precise holonomic robots for various applications in which multiple tools work precisely within the limited space of instruments and microscopes.

Vision Feedback Control for the Automation of the Pick-and-Place of a Capillary Force Gripper

In this paper, we describe a newly developed vision feedback method for improving the placement accuracy and success rate of a single nozzle capillary force gripper. The capillary force gripper was developed for the pick-and-place of mm-sized objects. The gripper picks up an object by contacting the top surface of the object with a droplet formed on its nozzle and places the object by contacting the bottom surface of the object with a droplet previously applied to the place surface. To improve the placement accuracy, we developed a vision feedback system combined with two cameras. First, a side camera was installed to capture images of the object and nozzle from the side. Second, from the captured images, the contour of the pre-applied droplet for placement and the contour of the object picked up by the nozzle were detected. Lastly, from the detected contours, the distance between the top surface of the droplet for object release and the bottom surface of the object was measured to determine the appropriate amount of nozzle descent. Through the experiments, we verified that the size matching effect worked reasonably well; the average placement error minimizes when the size of the cross-section of the objects is closer to that of the nozzle. We attributed this result to the self-alignment effect. We also confirmed that we could control the attitude of the object when we matched the shape of the nozzle to that of the sample. These results support the feasibility of the developed vision feedback system, which uses the capillary force gripper for heterogeneous and complex-shaped micro-objects in flexible electronics, micro-electro-mechanical systems (MEMS), soft robotics, soft matter, and biomedical fields.