Automation in the apparel and textile industry has long been a pursuit. However, accurately locating the surface of a fabric remains a challenge, limiting the automation in sorting, packaging, and other processes. When humans locate clothing, they rely on contact feedback for the exact position of the clothing surface. As existing contact detection solutions are significantly affected by environmental factors, it is essential to develop a sensor with robust contact detection capabilities. In this work, we introduce a contact sensor with high robustness and high force resolution. This contact sensor detects contact by measuring the deformation of an elastomer using a distancemeasuring module. Based on the deformation characteristics of the elastomer, we designed a detection algorithm that not only reduces the noise of data but also extracts features such as trends and elastomer states, enabling reliable contact detection. Through experiments, we validated that this contact sensor can detect contact forces as low as 0.017 N and is robust to external interference or sensor movement. We also verified that the sensor can process data within 7.5 ms and return contact detection with 95% accuracy. Additionally, we assessed its effectiveness in real fabric contact scenarios.

This study presents a wireless, integrated, and portable monitoring system for chronic obstructive pulmonary disease (COPD), featuring a highly sensitive and wide dynamic range MEMS-based flow sensor, alongside a high-accuracy respiratory monitoring algorithm. The flow sensor was fabricated using a CMOS-compatible MEMS process, achieving low power consumption (3.76 mW), high sensitivity (356.32 mV/(m/s)/W), and a wide dynamic range from -16.7 to 16.7 m/s. To meet the requirements of human respiratory monitoring and spirometric evaluation, a bypass channel was incorporated, enabling bi-directional flow measurement with an extended range of 11000 L/min. An abnormal respiration detection algorithm was developed based on critical respiratory parameters, including respiratory cycle, respiratory rate (RR), minute ventilation volume (MVV), and tidal volume (TV). Additionally, an enhanced interpolation method was integrated to improve the accuracy of spirometry testing, facilitating early-stage COPD screening. Experimental validation (1.13% volume error, average percentage error of -2.74% of all spirometry indicators) demonstrated that the proposed portable system delivers performance comparable to conventional, bulky medical spirometers, highlighting its strong potential for convenient, real-time respiratory monitoring and spirometric assessment in COPD management.

In[1], inaccuracies in several critical equations along with their accompanying descriptions appear in the article. Furthermore, some references are missing, and certain analyses of experiments are flawed.

The purpose is to optimize the Beetle Antenna Search (BAS) algorithm and apply it to the Intelligent Transportation System (ITS) to process traffic data in time and solve traffic congestion. This work studies the development status of ITS and the application status of the BAS algorithm. It optimizes BAS to converge to local optimization prematurely in high-dimensional space, affecting the prediction accuracy. Then, combined with the Least Squares Support Vector Machine Algorithm (LSSVM), the algorithm with quadratic interpolation optimization is proposed. The proposed algorithm is named the Quadratic Interpolation Beetle Antenna Search (QIBAS). On this basis, a traffic flow prediction model based on QIBAS-LSSVM is established. Finally, the improved QIBAS algorithm and Traffic Flow Prediction (TFP) model are verified. The results show that the test Mean Square Error (MSE) of the TFP model based on QIBAS-LSSVM increases by 4.28%, 7.38%, and 18.23%, respectively compared with the other three models. The test Mean Absolute Percentage Error (MAPE) increases by 0.09%, 0.06%, and 0.36% respectively. The proposed QIBAS algorithm has a good effect and high accuracy in short-term TFP. The research has important reference value for the digital transformation of transportation systems in modern smart cities.

This work aims to improve the transmission and sharing efficiency of intelligent transportation data and promote the further development of intelligent transportation and smart city. In this work, an EEMR (Energy Efficient Multi-hop Routing) is designed for the intelligent transportation wireless sensor network. In the EEMR algorithm, the base station runs the IAP clustering algorithm for network clustering after receiving the information of all surviving nodes. A method called ACRR (Adaptive Cluster-head Round Robin) is proposed for local dynamic election of cluster heads. In addition, the deep learning-based stochastic gradient descent algorithm and its evolution algorithm are sorted out, and its application in practical scenarios is analyzed. Due to the disadvantages of the adaptive algorithm in the current data processing process, the gradient optimization algorithm based on deep learning is adopted and the concept of adaptive friction coefficient is applied to the Adam algorithm to obtain a new adaptive algorithm (TAdam). The simulation experiment reveals that the proportion of network surviving nodes of the EEMR algorithm is still as high as 90% in 1,500 rounds of data collection. This shows that the EEMR algorithm achieves the energy balance of the network nodes as much as possible while minimizing the system energy consumption. In application scenario 1, when the network surviving nodes of the four data collection algorithms compares dropped below 40%, the number of surviving nodes in the EEMR algorithm is still as high as 97.6%. On the PTB (Penn Tree Bank) test data set, the TAdam algorithm shows the fastest convergence speed and the best generalization performance. The TAdam algorithm based on deep learning discussed in this work was of great significance for improving the transmission and sharing efficiency of intelligent transportation data.

Untethered miniature robots that can access narrow and harsh environments in the body show great potential for future biomedical applications. Despite the many types of millirobot that have been developed, swimming against the fast blood flow remains a big challenge due to lack of the ability to stay still and the large fluidic resistance from blood. This article proposes an on-wall-rotating strategy and a streamlined millirobot to achieve effective upstream motion in the lumen. First, the principle of on-wall-rotating strategy and the dynamic motion model of the millirobot is established. Then, a critical safety angle$\theta _{s}$is theoretically and experimentally analyzed for the safe and stable control of the robot. After that, a series of experiments are conducted to verify the proposed driving strategy. The results suggest that the robot is able to move at a speed of 5 mm/s against flow velocity of 138 mm/s, which is comparable to the blood flow of 2700 mm$^{3}$/s and several times faster than other reported driving strategies. This work offers a new strategy for the untethered magnetic robot construction and control for blood vessels, which would promote the application of millirobot for biomedical engineering.

Coupling the endface of an optical fiber to an integrated optical component is currently a low-throughput and costly manual process in the fabrication of the optical devices. In order to meet the high-volume demand for commercial optoelectronic devices, coupling must be automated. This paper presents a robotic positioning system and corresponding path planning strategy based on both the position and light intensity feedback. In this work, a micro-robotic positioning system with 3 degrees of freedoms (DOFs) is developed and integrated with an optical microscopy. Then the fuzzy controller is developed to design the trajectory. Lastly, simulation and experimental results demonstrate the accuracy and efficiency of the proposed system. Compared with the traditional manual method, the robotic positioning system can realize the coupling within 40 seconds. This method will have a significant impact on the automatic process of the micro manufacture field.

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 watchhand 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 × 10-3rad, which is enhanced at least two times compared with the traditional manual method.

Copper microwire is an essential metal widely used in micro-electron mechanical systems. Since micro/nano material usually demonstrates unique mechanical properties due to scaling effect, copper microwire mechanical properties need to be investigated for better adhibition. Herein, we propose a nanorobotics manipulation system for copper microwire insitu twisting test. Firstly, a system with six degree-of-freedoms (DOFs) nanorobotic manipulator integrated inside scanning electron microscope (SEM) is introduced. Secondly, a positioning and assembly method for copper microwire specimen are proposed to solve the mismatching problem. Finally, the copper microwire is twisted in-situ and its properties are investigated and analyzed. The copper microwire sample fracture morphology shows a severe plastic deformation and being along with the emergence of deformation twin and intertwine, which exhibit strong scaling effects. This system provides a new method for in-situ twisting test, which paves the way for mechanical characterization inside SEM and benefits the fundamental nanomaterial research immensely.

High-precision positioning is an essential requirement for sample operation at a small scale. At the current stage, although nanometer-scale accuracy has been achieved for the linear positioning, the rotational positioning (attitude control) is still very challenging and rarely addressed. This paper presents a rotatable nanorobotic system with rotational degrees of freedom first. Then, the system error, i.e., nonaxisymmetrical eccentricity error of the mechanism, is investigated dynamically and its fault model is established. After that, a double-loop servo repetitive controller is accordingly designed based on the circle interpolation strategy. The theoretical analysis and experimental results verify that the rotational positioning accuracy can be controlled up to submicrometers stably, which improves at least one order of magnitude than the current static method. Finally, two application cases are given to highlight the significance of this approach, i.e., surface defect detection from 360° and in situ twisting characterization of 1-D micro/nanomaterial. This research paves a new avenue for the ultrahigh rotational positioning at microscopy environment, which is expected to generate a long-term impact on the micro/nanofields, such as microscopy imaging, material characterization, and so on.

Scanning electron microscope (SEM) has been widely used for characterization and manipulation in micro/nano field. However, existing SEMs can only provide images for samples from one single direction. This limitation sometimes would lead to misleading results. In order to provide multidirectional SEM imaging, a nanorobotic manipulation system with a rotation robot is designed and integrated with SEM. During the robot's rotation, samples fixed on the robot can be viewed by SEM from multi-direction, instead of one direction. The rotation robot is able to rotate 360° along one rotation axis. To facilitate the multidirectional imaging, an automatic alignment method is put forward. This automatic alignment is to align samples to the rotation robot's rotation axis, so that during rotation, samples wouldn't move out of SEM's field of view (FOV). Alignment results are given to justify the proposed alignment method. Magnetic wires have been observed from multi-direction to demonstrate the nanorobotic manipulation system's potential application in mic.ro/nano defect study.

Microscopy has been an indispensable tool for micro/nanosample imaging, manipulation, and characterization. However, viewing the micro/nanosample from multidirection is still a big challenge for current microscopy. To address the above issue, this paper proposes a novel nanorobotic manipulation system for the automatic alignment and multidirectional imaging under microscopes. First, a miniature rotation robot with three degrees of freedom is designed and integrated with a microscope. Then, a forward-backward alignment strategy containing three loops, i.e., position shift loop, angle loop, and magnification loop, is proposed to align the sample to the rotation axis of the robot automatically. After that, the sample is imaged from multidirection by rotating the robot with one revolution (360°). Finally, the alignment accuracy is evaluated and multi-directional images of various samples are implemented. This study provides a new way for the microscopic imaging, which is expected to exert a significant impact in multiple fields on a small scale, including microscopy imaging, microdefect detection, micromanipulation, in situ characterization, and so on.

This paper introduces a novel catalytic mobile micro/nanorobot made only of platinum that realizes nanometer locomotion in hydrogen peroxide solution. The innovative mechanism and principle of the nanorobot are presented. A simple and effective fabrication process by focused ion beam and a stable manipulation method of the nanorobot are demonstrated. The nanorobot can steer or navigate by its finely designed geometry, and keep a stable rotational motion rather than arbitrary and uncertain movement. This paper evaluates the influence of some critical factors on the movement of the nanorobot, such as the concentration and temperature of the hydrogen peroxide solution, and the geometry of a nanorobot. The control of the nanorobot's movement can be realized based on the result of this evaluation. Compared with previous studies, this catalytic platinum nanorobot realizes bidirectional rather than unidirectional movement. The Langevin equation is used to describe the dynamic model of the platinum nanorobot.

3D tailor-made biodegradable scaffold integrated with biological cells or molecules is of great importance for tissue engineering. This paper addresses an improved method for exploring magnetic tweezers in patterning and aligning magnetic hydrogel fiber to fabricate large-scale engineered cell-hydrogel constructs. Magnetic hydrogel fibers were fabricated based on microfluidic device. The fabricated hydrogel fiber is made of alginic acid sodium and with a diameter of 34 μm. Magnetic nanoparticles is added into the alginic acid sodium solution to append magnetic material inside the fibers. The magnetic material inside the hydrogel fiber is regulated by the microfluidic device. Magnetic tweezers system based on solenoid electromagnet is utilized to evaluate the magnetic response of the magnetic hydrogel fiber. Evaluation results show the hydrogel fiber can be maneuvered by the proposed system with a positioning resolution of sub-micro level. The cultivation results of hydrogel fiber with C2C12 cells shows the potential for real applications of the proposed method in tissue engineering.

In this paper, an automatic system for single cell analysis inside an environmental scanning electron microscopy (ESEM) was proposed. Single yeast cell was put on an tungsten probe substrate inside ESEM. The endeffector for single cell analysis was fixed to an nanorobotic manipulator, which has three degrees of freedom, i.e. X, Y and Z translation. The real time images during the experiment can be observed by ESEM system in realtime. Therefore, the position of the endeffector and the single cell can be recognized by imaging processing. These position information were used as the feedback signal to control the movement of the nanorobotic manipulator. Finally, a single cell cutting experiment was performed to demonstrate the working mechanism of this system. Two types of cell pattern substrates were also designed and fabricated as the cell analysis chips for the automation single cell analysis in the future.

Single cell's mechanical property characterization is important for the understanding of the cell's condition and activity. In this paper, an automatic nanomanipulation system was proposed for single cell mechanical property characterization inside an environmental scanning electron microscopy (ESEM). A nanoneedle was fabricated from AFM (atomic force microscopy) cantilever by FIB (focused ion beam) etching technique. The nanoneedle was fixed to a nanorobotic manipulator, which has three degrees of freedom, i.e. X, Y and Z translation. Single yeast cell was put on an tungsten probe substrate inside ESEM. The position information of the nanoneedle and single cell were used as the feedback signals to control the movement of the nanorobotic manipulator. Finally, the stiffness of the single cell was measured using the nanoneedle driven by the automatic nanomanipulation system.

In this paper, a novel oscillating nano knife for single cell cutting at its native state was proposed. The nano knife with a small edge angle 5° was fabricated from a commercial AFM cantilever by focused ion beam (FIB) etching. The spring constant of the nano knife was calibrated by nanorobotic manipulation method. A piezo actuator was employed to generate the vibration of the nano knife. The oscillating amplitude response to the applied voltage was calculated based on the realtime image observation. Single yeast cell (W303) cutting using oscillating nano knife was performed based on the nanorobotic manipulation system inside an environment-SEM. The maximum cutting forces and the slices angle were measured from the deformation of the nano knife beam and the single cell. The result showed the oscillating nano knife was capable and effective for single cell cutting task.