Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Driver’s Distracted Behavior Detection Method Based on Multiclass Classification and SVM

To reduce the occurrence of traffic accidents caused by distraction. a detection method based on histogram of oriented gradient (HOG) and support vector machine (SVM) is proposed for driver’s distraction behavior in this paper. Interest region of driver was detected first from video image, also the image was enhanced, denoised and normalized. Then the histogram of oriented gradient is used to extract the feature of the image. Meanwhile, the cross-validation method is used to optimize parameters in SVM. Finally, the effectiveness of the method is verified by compared with classical SVM algorithm and Local Binary Pattern algorithm (LBP) based on SVM algorithms. The results show that, the proposed method can obtain better classification accuracy.
An Modified Real-time Photometric Calibration Algorithm Based on ORB Features*

In order to improve the accuracy of direct visual odometry and SLAM algorithm under illumination changes, we propose an modified real-time photometric calibration algorithm based on ORB features. Firstly, we use more robust ORB features as input to a optimization framework to obtain scene points correspondences. Then, we establish the reprojection pixels intensity residual equation based on photometric image formation and feature matching results of the camera. Finally, the incoming frames are corrected by the camera response function, exposure time and vignetting estimation. The proposed approach is tested with the EuRoC dataset and TUM dataset respectively, and experimental results indicate that the exposure compensation and time cost performances of the proposed method are promising.
Development of An Assist Upper Limb Exoskeleton For Manual Handling Task

In this paper we describe the construction of a wearable upper arm exoskeleton to provide support for industrial workers who engaged in repetitive handling tasks and patients who full or partial loss of function in their upper limb due to accident injuries, spinal cord and strokes. We use flexible rope driven by a motor to realize the shoulder and elbow joints linkage, use ball screw to realize the self-locking in any position to providing assist for users. This novel design not only saves energy but also make the whole system portable. The total weight of the prototype is only 2 kg. The exoskeleton is connected upper limb with 3 bandages, and users take about 30 seconds to put it on and 20 seconds to put the exoskeleton off without any help. The PD adaptive control method is applied to the proposed exoskeleton to track expected trajectories. Five healthy people participated in data acquisition. Upper limb muscle integrated electromyography (IEMG) of the deltoid muscle(DM), the biceps femoris muscle (BFW), the femoral muscle (FM), the femoral wrist flexor (FWF) were compared in continuous handling for four different loads (0, 1.5, 3, 4.5kg). The average assistance efficiency were 39.1%, 41.5%, 36.5% and 40.6% for the DM, BFM, FM and FWF respectively. The experimental data show that the upper limb exoskeleton can provide assist for workers and protect their upper limbs injuries in long-term handling task.
Planar Metasurface Lens based on Pancharatnum -Berry phase mechanism for efficient focusing

We present a novel subwavelength scatterer based on half wave plate principle, i.e., π phase retardation between two orthogonal polarizations. The scatterer has very small thickness around λ/20 and is capable to provide high transmission of cross-polarized circular polarized wave. The full phase control in the range of 0-2π is achieved by rotating the scatterer based on Pancharatnum-Berry Phase principle. The proposed scatterer is then utilized to demonstrate planar lens that could focus energy at the desired spot.
Representation of 3D Structure for Path Planning with Biped Wall-Climbing Robots

For biped wall-climbing robots, mapping and extraction of the parametric expression map denote challenging tasks, especially for the environments where lidar measurements degrade. To build a representation of the environment for global path planning, a three-dimensional (3D) planar structure modelling and parameterization system is proposed. The system includes the two following tasks: 1) mapping by a lidar-IMU fusion method in which point cloud registration algorithm tracks the lidar poses with the initial transformation matrix provided by IMU integration; 2) extracting the vertexes of planes that represent the parametric expression of the 3D planar structure. Experiments showed that our mapping algorithm was more rubust than others in the lidar-degraded environment. Besides, the precision analysis verified that the parametric expression map was accurate enough to be used for path planning of biped wall-climbing robots.
A Tendon-Driven Dexterous Hand Design with Tactile Sensor Array for Grasping and Manipulation*

This paper presents a tendon-driven dexterous hand with tactile sensor array. The proposed modularized dexterous hand that has optimized finger structure, tendon transmission and sensory system is introduced. The tendon path is optimized to reduce friction and the whole composition of finger is more compact. In order to maintain the tension of tendon, a novel tensioner is designed and mounted between the actuators and the hand. Then the high-density tactile sensor array is elaborated.It has the advantages of high measuring accuracy, high-density array, easy to install. Meanwhile, the control system of the dexterous hand is introduced. Finally several experiments are implemented to prove the effectiveness of the proposed tendon-driven dexterous hand.
A Survey on the Viability of Confirmed Traffic in a LoRaWAN

Internet of Things (IoT) deployments are on the rise globally with Low Power Wide Area Networks (LPWAN) providing the wireless networks needed for this expansion. One of these technologies namely Long Range Wide Area Network (LoRaWAN) has proven to be a very popular choice. The LoRaWAN protocol allows for confirmed traffic from the end device to the gateway (uplink) and the reverse (downlink), increasing the number of IoT use cases that it can support. However, this comes at a cost as downlink traffic severely impacts scalability due to in part a gateway’s duty cycle restrictions. This paper highlights some of the use cases that require confirmed traffic, examines the recent works focused on LoRaWAN confirmed traffic and discusses the mechanism with which is implemented. It was found that confirmed traffic is viable in small networks, especially when data transfer is infrequent. Additionally, the following aspects negatively impact the viability of confirmed traffic in large networks: the duty cycle restrictions placed on gateways, the use of spreading factor 12 for receive window 2 transmissions, a high maximum number of transmissions (NbTrans) and the ACK_TIMEOUT transmission backoff interval. The paper also raises and suggests solutions to open research challenges that must be overcome to increase the viability of confirmed traffic.
CNNs based Foothold Selection for Energy-Efficient Quadruped Locomotion over Rough Terrains

When deployed in practical scenario, the legged robot has higher terrain passing ability but is suffering from lower locomotion efficiency than the wheeled robot. In this paper, we present a strategy that can improve the locomotion efficiency for a quadrupedal robot. First, an optimized energy-efficient nominal stance is generated. Second, a Convolutional Neural Networks (CNNs) based and self-supervised foothold classifier is implemented which will guide the robot to form the supporting legs in energy-efficient nominal stance during locomotion. The effectiveness of the present approach is validated on our quadrupedal robot Pegasus in stairs climbing experiment.
Online Center of Mass Detection for Quadruped Robots in Trot Gait Motion*

Most of the motion control strategies for the quadruped robots are based on the trajectory planning of the center of mass (CoM) and the hypothesis that the CoM locates at the geometrical center of the trunk. In fact, the CoM position offsets will introduce obvious influence to the control performance. This paper presents a method for online CoM detection for quadruped robots running in trot gait. The dynamical model of the robot is built in the inertial coordinate system. Transforming methods for the status variables from the base frame to the inertial frame are also provided. To get more precise results, the step height compensation method for swing feet and comparative ground reaction force calculations are presented. With the proposed method, the analytical solution of the CoM position is obtained. Simulations show the effectiveness of the proposed method.
Acceleration and Implementation of Convolutional Neural Network Based on FPGA

Aiming at the problem of high power consumption and slow operation speed of neural network in embedded system, this paper presents an automatic design method of convolutional neural network (CNN) accelerator based on field programmable gate array (FPGA) to meet the requirements of embedded terminal for operation performance and power consumption. Firstly, in order to reduce the storage resources of the FPGA and the time required for network computing, the weight quantization method is used to convert network parameters from floating-point data to binary data. Secondly, in order to improve the speed and throughput of the whole system, coarse-grained and fine-grained parallel computing optimization methods are used. In this paper, the above acceleration scheme will be applied to the scene of unmanned aerial vehicle (UAV) object detection. The test results shows that the power consumption of the system is 2.38W and the calculated power consumption ratio is 29.3GOPS/W. Compared with the work of related literature in recent years, the proposed scheme can provide higher speed and efficiency. The experimental results show that the accuracy of the IOU is 21% and the speed is 7FPS.
Weld Seam Detection Method with Rotational Region Proposal Network

The traditional weld seam detection methods in passive vision are usually realized by detecting edges or textures of the weld seam. Since illumination conditions, weld seam types and backgrounds vary with tasks, these methods only work with specific weld types or environment. This paper raises a weld seam detection method that replaces the four main steps in traditional weld seam detection (pretreatment, thresholding, seam detection, seam fitting) with an end-to end neural network system. The method eliminates the ambiguity of original horizontal bounding box by adding an inclination parameter to the region proposal network (RPN). Compared with other methods in passive vision, our method is appropriate for accurate and fast detection of various types of weld seams in complex environment and meets the requirements for online seam detection of industrial robot.
Wideband Low-Profile Quasi-Yagi Antenna Using Artificial Magnetic Conductor

A wideband low-profile quasi-Yagi antenna operating above a metal surface is presented in this paper. The design approach combines a printed double-element quasi-Yagi antenna and an Artificial Magnetic Conductor (AMC) reflector, which can eliminate the negative effect of the metal on the antenna performance, such as impedance mismatch and low radiation efficiency. To verify the design, a prototype of the antenna is fabricated and the performance of the antenna, such as reflection coefficient and radiation pattern, are studied.
A Full-SIW Sequential-Rotation Feeding Network Based Ku-Band Wideband Circularly Polarized Array

A wideband high-efficiency circularly polarized (CP) antenna array is presented in this paper. With the specially designed broadband CP element and wideband full-SIW sequential rotation (SQR) feeding network, wideband high efficiency CP radiation can be achieved for the proposed array. For the proposed element, wideband CP radiation is obtained by loading an inhomogeneous superstrate in front of an SIW excited log periodic dipole array (LPDA). Then, a 2×2 array is designed based the wideband CP element and a simplified full-SIW SQR network is also introduced. In order to achieve a full-SIW array feeding, a wideband hybrid mode SIW feeding cavity is also proposed. Besides, by exploring the symmetric property of the LPDA dipole element for 180° phase shift, the SQR feeding configuration is further simplified. With the proposed array design method, simple structure as well as excellent array performance such as wideband CP operation, high-efficiency and wide gain bandwidth are achieved at the same time.
Design of A Lower Limb Exoskeleton Driven by Tendon-sheath Artificial Muscle*

In the past decades, with the development of science and technology, lower limb exoskeletons have been developed quickly, which can help patients to walk or do rehabilitation training. In this paper, the design of a lower limb exoskeleton, named SEU-EXO, will be presented in detail. The SEU-EXO is driven by a new type of artificial muscle, which actuated by a motor and tendon-sheath system based on Hill muscle model. In this structure, with a controllable clamper, a series spring and a parallel spring, this artificial muscle can mimics muscle’s characteristics, and has better compliance and controllability. Based on the principle of bionics, the degrees of freedom for rehabilitation exoskeleton are allocated reasonably, the mechanical structure is presented, and the tendon-sheath transmission path optimization method is studied. Finally, the evaluation experiments are verified, which proves the reliability and stability of the SEU-EXO.
Side Lobe Suppression of Marine-Radar Linear Array Antenna by a Reflectionless Metasurface

This paper demonstrates a side lobe suppression technique of a marine radar linear slot array antenna by a reflectionless metasurface. The metasurface introduces position-dependent phase shifts so that the phase across the entire aperture can be uniform. It is numerically shown that the metasurface drastically suppresses the maximum side lobe level at 9.41 GHz to be below -24 dB in both the E and H planes, and as a consequence, the peak gain of the main lobe is increased by 1.4 dB.
Design and experimental validation of a cable-driven continuum manipulator and soft gripper

In this investigation, a cable-driven continuum manipulator as well as its soft gripper are designed and developed. The continuum manipulator is made up of two sections, including nine threading plates and eight spring steels. The four cables from the top to the end drive the Section I to bend and deform. The other four cables from the middle to the end drive the Section II to bend and deform. The grasping force and the wrapping area are both considering into the topological optimization process of the soft gripper in order to get a satisfying grasping performance. Moreover, the experiment system including the continuum arm, the soft gripper, and the cable-driven control mechanism is developed. The grasping performance of the soft gripper and the motion control of the continuum arm are validated experimentally.
Harmonic Suppression of Microstrip Antenna by Defected Microstrip Structure

In this paper, a microstrip antenna with suppressed harmonics at 3.55 GHz is proposed. To achieve this operation, a short U-shaped defected microstrip structure (DMS) and a long U-shaped DMS are etched on the microstrip-feed line. The second harmonic can be reduced by using the long U-shaped DMS; meanwhile the short U-shaped DMS accomplishes the third harmonic suppression. The return loss of the proposed antenna at the fundamental, the second harmonic and the third harmonic frequencies are simulated and compared to that of the conventional microstrip antenna. It has been confirmed that the proposed antenna obtains outstanding harmonic suppression characteristic in the second- and third-harmonic frequencies.
Social Transparency in Enterprise Information Systems: Peculiarities and Assessment Factors

Social transparency within an organisation refers to the intentional sharing by individuals of information relating to themselves and their group to others in the workplace. This includes announcing personal interests, activity status, priorities and personal achievements. Such transparency is typically intended to increase relatedness, motivation and trust amongst colleagues. Social networking features are being embedded within organisational information systems, allowing an online version of social transparency. An ad-hoc implementation of such transparency can pose issues such as information overload, motivating unwanted grouping amongst colleagues and increasing pressure to perform in a certain manner. This results in organisational problems such as reduced productivity, unproductive competition and high turnover rates. Our ultimate aim is to address these issues by proposing an assessment method for online social transparency to detect and minimise its negative impact on employees and organisations. In this paper, we report on empirical study results and present (1) a set of peculiarities of implementing online transparency in enterprise information systems and (2) a set of essential factors that relate to the assessment process.
Underwater Object Recognition: A Domain-Adaption Methodology of Machine Learning Classifiers

This paper presents a novel dataset, composed of images of objects in two distinct environments and both controlled and uncontrolled capture conditions, aimed at serving as a benchmark for domain-adaptation image classification algorithms in an air versus underwater context. All images are fully annotated, extending the use of the dataset for detection as well as segmentation tasks. An exemplifying use-case is tested, where the performance of a Support Vector Machine applied to a Bag-of-Visual-Words and SIFT features is evaluated on both domains, with different training methodologies. Results demonstrate that the conventional classifier used has a lack of generalization ability, with a poor transfer of knowledge from the aerial to the aquatic domain.
Random Walk Network for 3D Point Cloud Classification and Segmentation

Object classification and segmentation via point cloud are essential for mobile robot navigation and operation. A lot of researches ranging from 3D voxels, mesh gird and multi-view were proposed based on point cloud. However, an accurate point cloud classification is still a challenging problem. Inspired by multi-label classification in images and convolutional neural networks (CNN), in this paper we present a novel network, named Random Walk Network (RWNet), which directly processes raw 3D point cloud data to classify points and, as a result, segment one 3D scene. State-of-the-art methods mainly focus on the features of one point while spatial relationships are also essential in point classification. To deal with this issue, we combine both appearance features and spatial information of feature points to restrain the point cloud processing. We employ PointNet first to generate initial point labels and adopt point labels with high confidence as seeds. We then construct the similarity matrix between seeds and low-confidence-labeled points according to their structural and spatial similarity and use Random Walk to obtain the final classification. We demonstrate our method in 3D classification task in various scenes and compare with some benchmark methods. Experimental results show that RWNet has a better performance than others.
A Magnetically Actuated Octopus-like Robot Capable of Moving in 3D Space

Magnetic driving is an excellent non-contact method that can penetrate through the human and the biological tissues without any damage. Also, micro-nano robots are expected to enter into the human body, which will bring about revolutionary development in robotics. Here we propose an octopus-like soft robot that is expected to be used in biomedical and engineering fields in the future. Firstly, we establish a magnetic control system, which uses the minimum number of coils. The system can respond quickly with high precision and can propel robot in 3D space utilizing the coupled field contributed by multiple electromagnets acting in concert. Based on the system, we designed an octopus-like robot with three legs. The robot can move freely without constraints in the workspace. We apply triangular wave gradient magnetic field, which makes the movement of the robot more stable and controllable. At the same time, the swing of the tail increases the moving precision of the robot and make the control easier.
Salient Object Detection based on Multiple Priors Fusion*

Salient object detection can be utilized to detect the most significant regions in various environments, which has been regarded as foundation of computer vision. Different saliency models use different prior or knowledge. We propose a multi priors fusion method for saliency measure, which integrates background prior with foreground prior and center prior. Firstly, through each boundary of the image, we can get four saliency maps, and fuse them to get the background prior saliency map. Secondly, we utilize boundary extension method to highlight regions, and these regions can be regarded as the queries of manifold ranking for the foreground prior saliency map. Thirdly, the corners on the image are obtained, filtered by the foreground region, and then clustered into a point as the center of Gaussian model, which is used to calculate the center prior saliency map. Finally, the above three kinds of prior-based saliency maps are fused via the proposed fusion framework to gain a better final saliency map. Compared with fifteen methods, the experimental results on ECSSD and MSRA10K show that our proposed method achieves better saliency detection results.
Electromagnetism Force Feedback Control of Bionic Grippers for Robotic Endovascular Intervention System

At present, the operation of most Robotic Endovascular Intervention (REI) can only through visual feedback, that is, the operator can only observe the situation on the scene through the X-ray equipment, and issue manipulation commands according to the observed scene conditions. Although the master-slave system with force feedback has made significant progress, some essential problems still need to be solved, especially the complicated structure and large external dimensions, which gives the operator a strong sense of weight and affects the sense of teleoperation. For a high safety of remote operation, this research proposed a kind of REI with bionic grippers and developed a prototype to verify its expectation of telepresence. The REI used the sliding table and steel wire to realize the forward and backward delivery of guidewire and catheter, and the bionic grippers were used to accomplish the twisting of guidewire and catheter imitating hands and fingers of human. A high-resolution force sensor is used to acquire the intervention resistance on bionic grippers, and a loading mechanism composed of electromagnetic coil, handle, and spring will reproduce the resistance on the doctor’s fingers through the handle. Laser displacement sensors and Rotary encoders are used on a master manipulator to control the movement and rotation of slave grippers. The experiments show that force feedback precision can reach 0.03 N, and response delay is less than 100ms when the frequency of the loaded force is above 3Hz. This research has laid a necessary foundation for REI technology.