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The recent development of 2D lamellar membranes may lead to the next generation of membrane processes for molecular separation, but smart regulation of substance permeability has rarely been report...

Ordered lamellar hybrid membranes are of great interest, due to their application as functional materials, including molecular sieving, biosensors, optical devices, and drug, as well as gene delive...

Making photoinitiators water-borne and polymeric represents the important advances in photo-curing fields. We, here, reported the design and preparation of a supramolecular polymeric photoinitiator by using the amphiphilic hyperbranched poly(ether amine)s (hPEA) as the host polymer, which can encapsulate guest photointiators via supramolecular interactions. Three kinds of amphiphilic hyperbranched poly(ether amine)s (hPEA101, hPEA211 and hPEA101-EO) were selected as the hosts for the supramolecular system and hydrophobic hydrogen abstracting photoinitiators with carboxyl groups (ATX, CTX, MATX and ABP) were used as the corresponding guests. The resulting supramolecular photoinitiators (hPEA@PIs) exhibit enhanced solubility both in an aqueous solution and acrylate monomer. Moreover, hPEAs have very high loading capacity (Cloading) for the photoinitiator in aqueous solutions. The photopolymerization kinetics by photo-DSC indicated that this supramolecular photoinitiator (hPEA@PI) can initiate the photopolymerization of a water-soluble monomer, namely acrylamide (AM), rapidly and effectively in water. In addition, the host hPEAs in addition can increase the solubility of the photoinitiator in organic solvents, and in particular, significantly enhance the compatibility between the photoinitiator and acrylate monomers. The hPEA@PI can also photoinitiate the polymerization of hexanedioldiacrylate (HDDA) and trimethylolpropanetriacrylate (TMPTA) with high double bond conversion (DBC). This strategy of using a supramolecular photoinitiator provides a facile approach to get an amphiphilic polymeric photoinitiator with good dispersion in water and oil systems, which will be potential in photo-curing fields.

The lower extremity rehabilitation exoskeleton provides a priceless opportunity for paraplegics to stand up and walk normally. In this paper, a framework for human-exoskeleton interaction with sEMG interface and electrotactile feedback is presented. Firstly, the exoskeleton recognises human motion intention through the Long Short Term Memory (LSTM) Neural Network based on surface electromyogram (sEMG). Secondly, electrotactile based on spatiotemporal coding scheme feeds back the exoskeleton states to the sensory skin, as a compensation for paraplegic's absent proprioception in lower limbs. Thirdly, physiological information, i.e. muscle fatigue, of arms is monitored and quantified with sEMG. Three healthy subjects participate the experiments including the motion intention recognition experiment, electrotactile perception experiment and online exoskeleton experiment. The online exoskeleton experiments demonstrate the feasibility and efficiency of the proposed framework. Furthermore, it is proved experimentally that the performance of collaborative control in rehabilitation human-exoskeleton interaction can be facilitated via the framework.

Reliable environmental context prediction is critical for wearable robots (exoskeletons or prostheses) to assist terrain-adaptive locomotion. Inspired by the mechanism of human perception of the environment, the vision sensor can be introduced into the soft lower limb exosuit robot so that future environmental information can be used to improve the control. In this paper, a stable terrain classification and recognition system (TCRS) is designed for lower-limb soft exosuit robots. When the exosuit robot perceives the environment, it uses the residual network to train the terrain classifier to classify the terrain. During walking, the wearable soft exosuit robot collects the indoor environment, preprocesses, and marks the sampled images separately. The experimental results show that the classification accuracy is more than 90%, and the highest is 97.5%. The results in this study may lead to novel context recognition strategies in reliable decision-making, efficient sensor fusion, and improved intelligent system design in various applications.

This paper proposed a framework of cooperative UAV-UGV system. This system consists of three modules: UAV, UGV, and ground station console. It has the characteristics of high cohesion, low coupling, cross platform, and cross language. Compared with the prior methods which UAV-UGV cooperation system that only uses UAV to track UGV, our method is more effective and can give full play to the advantages of UAV and UGV. We use UAV visual tracking algorithm and coordinate transformation to get the target location, and use UGV to navigate to the target location to keep up with the target. The high mobility of UAV makes the target tracking range of the whole system larger, the robustness of UGV is good, and the tasks can be performed more precisely.

A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism.

With the increase of the world's population and the serious aging phenomenon, more and more people with mobility impairments need technology to assist them in their daily lives. Autonomous Exoskeleton are one of the important technologies. The existing gait generation algorithm are most based on simplified mathematical model calculations, which have the problem of poor accuracy and unfriendliness to the wearer. This research aims to propose a path planning and gait generation policies (HPPO) based on hierarchical reinforcement learning (HRL), so that the wearer can safely avoid obstacles and maintain dynamic balance when using the autonomous exoskeleton controlled by this policy to walk. The high-level controller (HL) is responsible for path planning, it can quickly plan a reasonable exoskeleton footholds in the indoor environment. The low-level controller (LL) can imitate a given reference trajectory, learn a walking policy suitable for the exoskeleton, and it can follow the planned footholds, so as to achieve the purpose of avoiding obstacles for the wearer. The algorithm is verified in simulation environment.

Measuring the three-dimensional (3D) deformation of submerged objects through different media with the stereo digital image correlation (stereo-DIC) method involves the refractive optical imaging problem where the non-linear transmission of light is induced by a change of medium density. The problem invalidates the underlying single viewpoint assumption of the perspective model in regular stereo-DIC, thereby resulting in erroneous measurements of 3D shape and deformation. In this work, we propose a refractive stereo-DIC method that overcomes the problem by considering light refraction in 3D reconstruction. We formulate a full refractive reconstruction geometry description based on Snell’s law of flat refraction and the regular triangulation. This allows the true shape to be effectively reconstructed by tracing and establishing the refracted ray-paths based on the regular 3D reconstruction, without reformulating the camera model and image formation. The refractive stereo-DIC is finally established by integrating the refractive 3D reconstruction into the regular DIC framework for measuring accurate 3D shape and deformation of submerged objects. We experiment the proposed approach with underwater 3D shape and deformation measurements. Both results prove its feasibility and correctness, further heralding our approach as a flexible solution that could readily extend the stereo-DIC to fluid-immersed 3D deformation characterization.

Camera calibration is crucial for geometric vision-based three-dimensional (3D) deformation measurement tasks. Among existing calibration techniques, the one based on planar targets has attracted much attention in the community due to its flexibility and reliability. Our study proposes a calibration technique to obtain high-accuracy internal and external parameters based on low-cost ordinary planar patterns. The proposed method determines the optimal internal parameters for each camera by refining 3D coordinates of planar control points, where an analytic model of optics distortion is presented to enable lens distortion to be corrected directly in subsequent external calibration and underlying 3D reconstruction. External parameters are estimated by minimizing a bundle adjustment framework, which is carefully designed based on the proposed distortion correction model and depth parameterization. In contrast to the existing techniques, the proposed method is capable of obtaining a high-accuracy calibration with ordinary targets rather than the well-designed and fabricated ones. We experimented the proposed method with a calibration performance analysis and a displacement measurement; both results demonstrated the accuracy and robustness.

Calibrating stereo digital image correlation (stereo-DIC) is crucial for 3D deformation measurements. Existing stereo-DIC calibration methods mainly rely on a well-made planar target with additional specific coding to perform pre-calibration. In this paper, a new method is proposed to calibrate a stereo-DIC system automatically with feature correspondences in an unconstrained scene. In contrast to traditional methods, the proposed method is scale-independent and does not require assumptions such as planarity. More importantly, it is capable of correcting disturbed external parameters in real time. With inverse depth parameterization, a stereo-DIC system can be effectively calibrated by a carefully designed bundle adjustment framework. Subsequently, a fast correction strategy based on massive-point subset tracking is derived to recalibrate the disturbed stereo-DIC system. The proposed method overcomes the predicament of reduced measurement accuracy due to the unavoidable disturbance of external parameters in dynamic deformation measurements. Experiments were conducted to verify the effectiveness of the proposed method.

We propose an adaptive filter method based on a deformable window shape to remove the noise of wrapped phase fringe patterns in electronic speckle pattern interferometry (ESPI). The filter kernel automatically adjusts its size, shape, and direction according to the direction and curvature of the phase fringe pattern. The direction of a phase fringe pattern is determined using a gradient-based method. Fringe curvature is estimated based on the calculated direction and fitted phase contours. Simulations were performed to evaluate the proposed method, and the results were compared with those of the 2-D windowed Fourier transform filtering (WFTF) algorithm and the medial filter technique. Simulated and experimental results show that the new approach can provide more effective de-noising for phase fringe patterns compared to the other two methods, using few parameters.

Dynamic complex surface topography with ordered and tunable morphologies, which can provide on-demand control of surface properties to realize smart surfaces, is gaining much attention yet remains challenging in terms of fabrication. Here, a facile, robust, and controllable method is demonstrated to fabricate programmable two-dimensional (2D) ordered patterns with multiresponsive 2D ultrathin materials, comprised of anthracene-capped hyperbranched poly(ether amine) (hPEA-AN)-functionalized graphene (hPEA-AN@G). By combining the stimuli-responsiveness and UV sensitivity of hPEA-AN and excellent out-of-plane deformation and NIR-to-thermal conversion of graphene, the process of "writing/uploading" initial information is conducted through the initial exposure to 365 nm UV light to generate the 2D ordered pattern first; second, inducing swelling strain via moisture to create the hierarchical topographic pattern (orderly oriented pattern) is the process of "modification and erasable rewriting"; third, alternating NIR or 254 nm UV light blanket exposure are the two ways of erasing the information. Consequently, taking advantage of the multiresponsive dynamic wrinkling/ordered patterning, we can program globally 2D ordered surface patterns with diverse morphologies on demand and manipulate the resulted surface properties as desired.

This paper proposed a method to detect cliff edge by using an RGB-D camera, and then to fuse the cliff information with LiDAR, finally to provide navigation information for robot autonomous exploration and autonomous movement. Compared with the prior methods which set sonar or infra-red sensor in the bottom of the robot, our method could detect cliff earlier by set the RGB-D camera forward. In cliff detection, we use region growing algorithm and the normal vector of plane to segment out ground plane in point cloud, then extract the boundary points of ground, and we proposed an Edge Point Filter (EPF) to get the edge points of cliff, then use the edge points to simulate LiDAR data and combine with real LiDAR data to mark the untraversable area. We verified the practicability of this method in simulation, and verified the accuracy with real sensors.

Real-time monitoring of structural health conditions for rotary objects is of importance for safety assessments. In this work, an efficient algorithm based on digital image correlation is presented to achieve accurate rotational matching in real time. The proposed algorithm measures rotation in object motion with an integer pixel search followed by a subpixel correlation refinement. In the integer pixel search, the reference subset is rotated inversely to facilitate the correlation computation between the reference and target subsets. Then an independent and global integer pixel search for each point of interest is performed by applying the particle swarm optimization algorithm. Finally, a modified iterative registration algorithm is introduced to refine the displacement in the subpixel level by considering both the rotation angle and displacement components. Simulation and rotation experiments demonstrate that the proposed method achieves rapid and accurate measurements and is an effective method for retrieving the rotation data of rotating structures.

Infrared thermography (IRT) is a full-field, contactless technique that has been widely used for nondestructive evaluation of structural materials due to many advantages. One of the major limitations of IRT is the fuzzy edge and low contrast in the inspected images&mdash, as well as the cost of the system. An efficient image post-processing with an affordable and portable device is of great interest to the engineering society. In this study, a convenient and economical inspection system using common halogen lamps was constructed. The corresponding image-processing scheme, which includes Fourier phase analysis and specific image enhancement was developed to identify defects with sharp and clear edges and good contrast. This system was applied to localized of defects in glass-fiber-reinforced composite panels. The results showed that defects with an effective diameter as small as 5 mm can be detected with excellent image quality. As a conclusion, the developed system provides an economic alternative to traditional infrared thermography which is able to identify defects with good qualities.

Recovering the geometric shape of deformable objects from images is essential to optical three-dimensional (3D) deformation measurements and is also actively pursued by researchers. Most of the existing techniques retrieve the shape data with triangulation based on pre-estimated stereo correspondences. In this paper, we instead propose to recover depth information directly from images of a binocular vision system for 3D deformation estimation. Given a calibrated geometry of the system, the reprojection error is parameterized by the depth and then described with local intensity dissimilarity between a stereo pair in considering spatial deformation. Afterward, a correlation adjustment model is formulated to estimate the depth parameter by minimizing the error. As a solving strategy, we show the Gauss-Newton linearization of the proposed model and its initialization. 3D displacement estimation based on depth information is also presented. Experiments, including rigid translation and bending deformation measurements, are conducted to verify the performance of the proposed method. Results show that the proposed method is accurate yet precise in 3D deformation estimations. Other underlying developments are underway.

Stereo digital image correlation (stereo-DIC) technique shows a powerful capacity on full-field three-dimensional (3D) deformation measurement of rotary machine structures. However, it remains a challenge for underwater applications due to difficulties in imaging, stereo calibration, light refraction, and so on. In this paper, its potential in characterizing 3D dynamic deformation of the underwater rotor blades is shown by solving these problems. A stroboscopic stereo-DIC system is established to capture clear speckle images of a blade that rotates in the windowed cavitation tunnel under different flow speeds. To calibrate the stereo camera for underwater object measurement, an improved planar pattern-based calibration method and a globally optimal relative pose estimation algorithm are proposed to calibrate the intrinsic and extrinsic parameters of the stereo-DIC system separately. In particular, a novel refractive 3D reconstruction method for underwater objects is presented to recover the true 3D shape according to flat refraction geometry, ensuring the correctness and reliability of the measured 3D displacement fields. Several experiments demonstrated that the proposed stereo-DIC system and methods are feasible and accurate. Based on this, the measured dynamic displacement fields of a propeller blade are presented and discussed. Results herald a possibility for monitoring the full-field 3D dynamic response and structural health of underwater rotating structures by the proposed technique.

To make photoinitiators (PI) to be polymeric and water-soluble is an effective approach to develop the high efficient photoinitiator systems with low-migration, low-toxic and environment-friend. We developed a series of novel amphiphilic hyperbranched polymeric photoinitiators (hPEA-TXs, and hPEA-BPs) by introducing thioxanthone (TX) or benzophenone (BP) moieties into the periphery of the hyperbranched poly(ether amine) (hPEA) comprised of the hydrophilic poly(ethylene oxide) (PEO) short chain and coinitiator amine moieties in the backbone. Compared with their water-soluble low-molecular weight analogues, the resulting hyperbranched polymeric photoinitiators hPEA101-TX, hPEA211-TX, hPEA101-BP and hPEA211-BP could be dissolved very well not only in many organic systems including acrylate monomers, but also in water with high solubility of 10 wt%. The photopolymerization kinetics of water-soluble monomer acrylamide (AM) and three hydrophobic multifunctional acrylate monomers initiated by these hyperbranched photoinitiators were investigated in detail by photo-differential scanning calorimetric (photo-DSC). Both hPEA-TXs and hPEA-BPs can initiate photopolymerization of AM as efficiently as their low-molecular weight analogues MGA-TX and MGA-BP, respectively. The final double bond conversion (DBC) of oil-soluble monomer hexanediol diacrylate (HDDA) photoinitiated by these hyperbranched photoinitiators can reach as high as 99%. Especially for photopolymerization of multifunctional monomers initiated by these hyperbranched polymeric photoinitiators, the final DBC of trimethylolpropane triacrylate (TMPTA) and pentaerythritol tetraacrylate (PETTA) can reach 80% and 60%, respectively, which is much higher than that of low-molecular weight photoinitiators.

Thermography and shearography are optical techniques for detecting and characterizing subsurface defects in structures. Both techniques possess unique advantages and abilities, as well as limitations, based on their distinct mechanisms. In this study, the feasibility in fusion of thermography and shearography is explored. Thermal excitation is selected to induce temperature variation and out-of-plane deformation on the object surface, acquiring the shearography phase maps and thermography image sequence simultaneously. Infrared images are dealt with by the Fourier phase analysis incorporate with an edge-aware filter. Fusion of the detecting images is obtained by performing a projective transform between each pair of the thermography and shearography images. Subsequently, both thermography and shearography images are separated into detail and background images. The fused image is reconstructed from the detail and background images by applying a weighting function. Experiments have indicated that the proposed method is effective in identifying defects by combining two image-based NDT methods.

Hierarchical patterns are playing an increasing role for various fields due to their integrated functions. Herein we created a novel library of multi-scale complex patterns where hierarchical wrinkles can be dynamically generated and eliminated by in situ photo-control. Atom Force Microscopy (AFM) results and UV-vis kinetics manifest that the change of surface modulus induced by dynamic photo-dimerization of the anthracene-containing polymer (PAN) top-layer plays a crucial role in triggering the morphology switch of the resulting wrinkled surface with self-healing, tunable adhesion and wettability properties. Based on the temporal and spatial characteristics of dynamic photo-dimerization, the ordered and hierarchical patterns can be obtained through adapting selective exposure and photolithography. Furthermore, a series of hierarchical patterns in which the smaller-scale wrinkles can be prescriptively generated on the assigned micro-pillar arrays, making up sets of Braille characters, was demonstrated for Braille text refreshable typography through photo-reversible formation and erasure. This novel and effective approach for photoreversible hierarchical wrinkle patterns offers great promise for smart devices and surfaces with dynamic tunable morphology and surface properties on demand in response to light stimuli without altering the bulk properties.

A novel type of supramolecular hydrogel was developed by in situ polymerization of acrylic acid (AA) and acrylamide (AM) monomers in the aqueous solution of chitosan (CS), in which nanofiber-structured CS and polyelectrolyte chains of poly(acrylic acid-acrylamide) P(AA-r-AM) form the dynamic cross-linked network through the electrostatic interaction of ions. 1H NMR, WAXD, SEM and TEM were used to trace the formation of this supramolecular hydrogel, and revealed that CS chains aggregate into a nanofiber when the copolymerization of AA and AM proceeded. The obtained hydrogels exhibited good comprehensive mechanical properties. With the excellent fatigue resistance and a high toughness of ∼500 J m−3, the tensile strength and elongation of hydrogel-5 are 120 kPa and 1600%, respectively. The obtained supramolecular hydrogel can self-heal and exhibited no residual strain after continuous deformation-resting processes and loading–unloading tests. Furthermore, the obtained hydrogels can be used to adsorb metal ions in water, interestingly their tensile modulus enhanced several times after adsorption of metal ions.

Polymer sponges with molecular recognition provide a facile approach to water purification and industrial separation with easy operation, but its fabrication is still challenging because some critical issues of selective adsorption, high mechanical strength, and easy collection/re-use are difficult to be achieved in one material. Here, inspired by natural sponges, novel multifunctional polymer sponges were developed which were fabricated by ice-templating with multifunctional amine polyethylenimine and diepoxide cross-linker poly(ethylene glycol) diglycidyl ether for highly efficient harvesting of dyes and simultaneous pure water recovery both in mechanic pressing and filtration processes. The as-prepared sponge (SP-1) was further modified by poly(caffeic acid) through a simple dipping-cross-linking process to obtain the hybrid polymer sponge (SP-2), which showed higher compressive strength than SP-1. These sponges possessed a cross-linked three-dimensional macroporous structure with quick water absorbing properties over ten times of their own weight within 20 s directed by capillary. The adsorption behavior of the obtained polymer sponges to 11 hydrophilic dyes was studied in detail by mechanic induced separation. All these polymer sponges exhibited a high selective adsorption to hydrophilic dyes in water. For example, SP-1 has high adsorption capacity over 150 μmol/g to erythrosin B, which is 20 times higher than that of calcein. With the modified poly(caffeic acid) layer, SP-2 exhibited different adsorption properties for methylene blue (180 μmol/g) to SP-1 (∼0 μmol/g), indicating that the tailorable structures of the sponge can regulate their selectivity to guest molecules. Based on the unique recognition to guest molecules, the methodology of dynamic separation of the dye's mixture in water was demonstrated by using these sponges through mechanical pressing or fast filtration, which provides a facile alternative with easy operation for water purification.

We propose a method to reconstruct a High-Definition Color-Pointed map from the large-scale urban road scene. In contrast to prior methods, we collect the urban road data under the severe traffic conditions and several kilometers long data sets. In our High-Definition Color-Pointed map, we can clearly see the lane surface and surrounding environment. Moreover, our maps are collected in a high speed of 40km/h, which greatly improved the practicality of the whole system. The High-Definition Color-Pointed map can be used in perception, localization and automatic navigation in driverless cars, drones and smart city management. Images, lidar and gnss best poses are collected as the raw data. We use interpolation method to process the raw data, and use our algorithm to translate the Lidar poses into the images collected time. To detect the dynamic obstacle, we use the fast neural framework YOLOv2. Our method, Dislocation Projection, can solve the spare points problems. Our algorithm was evaluated on wide roads and narrow streets. The experimental results exhibited the effectiveness of the proposed approach.

Circular markers are widely used in image-based measurement fields, e.g. vision system calibration, displacement measurement, and vibration monitoring. Generally, the marker positioning error inevitably leads to inaccurate results. As one of the key factors, the non-uniform illumination seriously affects the localization precision of circular markers. In order to reduce the influences of uneven lighting, a homomorphic filtering-gray weighted centroid method (HF-GWCM) is presented in this work. Firstly, the basic principles of both HF and its combination with GWCM are introduced. Subsequently, some simulation examples are conducted to analyze the localization accuracy of concentric circle markers under non-uniform illumination situations, which comprise the influences of HF parameters and different localization methods. Finally, a single camera imaging system with multiple light sources is employed to perform some tests for the effectiveness validation of HF-GWCM. Both positioning accuracy and stability of HF-GWCM are analyzed under different uneven illumination situations, including lighting movement, multiple light sources, and shaded region. Results demonstrate that HF-GWCM owns the ability to resist the interference of non-uniform illuminations, and it is also an effective way to improve the localization accuracy of circular markers.

Calibration of a stereo vision system is essential for three-dimensional shape and deformation measurements. Although the target-based calibration technique is a good solution, it comes with limitations in a large field of view (FOV) measurement due to the target size and difficulties in operation. In this paper, a method using the inertial measurement unit (IMU) has been proposed to calibrate stereo vision systems for large-scale measurements. The prerequisite for this method is to calibrate the camera intrinsic parameters in advance. With the alignment of IMU sensor with the camera, the relative rotation between the two cameras can be determined through coordinate transform. An angular differential method has been developed to improve accuracy in determining the yaw angle. After the epipolar geometry is constructed upon stereo scene correspondences, the translation vector can be obtained by solving a set of linear equations, since the intrinsic parameters and the relative rotation are predefined. The proposed method does not require any known calibration target, leading to easy operation in practice. Two laboratory experiments are presented to demonstrate the use of the method. The experimental results show that the accuracy of the proposed method is comparable to that resulted from the well-known Zhang's method, and it can also be applied to measurement with a large FOV.