Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Vortex Beam Propagation Properties with the Ground Reflection

In this paper, the propagation properties of the vortex beam carrying orbital angular momentum (OAM) with ground are analyzed. When the vortex electromagnetic wave propagate in the real environment the reflected electromagnetic waves from the ground can affect the propagation and reception of the vortex beams. A uniform circular array (UCA) antenna is designed at 10GHz for generating the vortex beams. The corresponding electric field distribution, including the amplitude distribution and phase distribution of the vortex electromagnetic wave in some specified position is presented, and the corresponding OAM mode spectrum distribution of the vortex beam is calculated. Finally, the corresponding conclusions are summarized. These analyses could provide some references approaches for the vortex beam related studies such as in the area of radar and wireless communication.
A Compact Monopole Antenna With Filtering Response for WLAN Applications

A novel compact monopole antenna with filtering response for WLAN applications is presented in this paper. The antenna is composed of a capacity-loaded matching patch, two resonators, and two end-coupled monopoles. The resonators consist of wide rectangular patches and narrow shorted lines to form the resonance, and the resonators are printed on the different layers to increase the design flexibility. Two meandering monopoles are located at the edges of the top layer with capacitive coupling at each other's end. The mutual couplings between the meander monopoles are utilized to produce two radiation nulls at the two band-edges. Based on the design method, the prototype of the proposed antenna was designed, fabricated and measured. The measured results show that the antenna has a broad bandwidth of 16% for S11<−10 dB. Also, ideal omnidirectional radiation patterns, and steep band-edge selectivity with two radiation nulls are achieved for the proposed antenna.
Kinematics Analysis of a Hybrid Robot Consisting of a SCARA and a Parallel Wrist

For some manipulation tasks needing to change objects’ orientation and position quickly, a hybrid robot, consisting of a 4-DOFs SCARA and a 3-DOFs (2R1T) parallel wrist, is presented. First, the swing and translation characteristics of the parallel wrist are quantitatively analyzed by numerical method, and its maximum swing angle and optimum working curve are obtained. A swing-rotation method for representing the attitude of the parallel wrist is proposed, and it can be transformed with the commonly used Azimuth-Swing method, which is the key to decouple kinematics of hybrid robots. Then, the singularity of the mechanism, when its attitude expressed by the proposed method, is also analyzed. The forward and inverse kinematic equations are derived in an analytical form. Finally, the kinematics simulation based on ADAMS verifies the correctness of the robot kinematics.
Energy Efficient Swing Leg Trajectory Planning For Quadruped Robots Walking On Rough Terrain

When the quadruped robots perform some patrol and rescue missions, they have to stay outdoors for a long time. Therefore, energy consumption should be reduced as much as possible to improve the robot’s endurance ability. In this paper, we analyzed the energy consumption of the electric quadruped robot in the swing leg phase and presented a swing leg trajectory optimization approach which is both collision-free and energy-efficient on rough terrain. The effectiveness of this trajectory has been verified by the experiments in which our quadruped robot Pegasus crossed obstacles such as steps, slopes, and stairs automatically. The experiments have been carried out both in computer simulation and the robot Pegasus.
A Monocular Target Pose Estimation System based on An Infrared Camera

We present an accurate and robust pose estimation system based on infrared reflective markers and a monocular camera with an infrared filter. The infrared reflective markers are pasted on target object and the camera is mounted on the mobile robot. In the system initialization phase, the correspondence between the markers and image observations are calculated by our correspondence search algorithm. After the initialization, correspondence between markers and observations can be predicted with pose computed in last frame. Thereafter, P2P algorithm based on LevenbergMarquardt is applied to optimize the pose of the current frame. The experiment result shows that our system has larger positioning range than ArUco markers. In addition, this method can estimate object pose in most perspective and is robust to occlusion.
Design and Modeling of a 2-DOF Cable-Driven Parallel Wrist Mechanism

This paper proposes a novel design of 2-DOF Cable- Driven Parallel Wrist Mechanism (CDPWM). This mechanism can achieve hemispherical movement in space which has a unconventional twin actuation. The configuration has a great flexibility (with no singular points within the entire motion range), and a large stiffness of 1.07 × 106 Nmm/rad. This work utilized a vector analysis method to establish the kinematic model of this construction and the stiffness performance of the mechanism was also analyzed. The proposed model can deeply simplify the kinematics solution of this type of cable driven system with a maximum position error of 0.03 mm. Based on this method, the velocity Jacobian of the mechanism was also constructed. Then the stiffness of the mechanism was theoretically modeled, and validated through the finite element method (FEM).
Design Strategy for a Surgical Manipulator based on a Compliant Mechanism : Rigidity and Range of Motion: Finding the Optimized Balance

Compliant mechanisms have drawn the attention recently in developing surgical robotic manipulators for minimally invasive surgery (MIS) owing to their capabilities in making miniaturized, simple, dexterous mechanical structures. Robotically assisted MIS demands instruments with higher precision, higher output force and a higher range of motion (ROM) for better performances. On the other hand, because of the behaviour of the elastic elements, compromising these factors is challenging. In a compliant mechanism, the rigidity of the elastic element determines the precision and output force. In this paper, we study the behaviour of rigidity and the ROM of elastic elements using previously developed surgical robotic forceps based on a compliant mechanism. To tackle this problem, we studied the variation of ROM of the compliant mechanism at different rigidity values of the compliant structure by changing its thickness. The results showed the linear relationship between the ROM and the rigidity of a compliant mechanical manipulator, suggesting the optimized balance point in this trade-off.
Trajectory Optimization and Force Control with Modified Dynamic Movement Primitives under Curved Surface Constraints*

Dynamic Movement Primitives (DMPs) have been used extensively for trajectory planning due to robust against perturbations and excellent generalization performance. However, canonical discrete DMP could not generate right trajectories in three cases: the goal point is same as the start point, the goal point is close to the start point, and the goal point is changing across the start point. Moreover, when the original trajectory is on a curved surface, it is difficult to ensure that the generalized trajectory remains on this surface. In this paper, we propose a modified DMP method with the scaling factor and acceleration coupling term to solve the policy of the above learning problems using redundant robots. First, we introduce the adjusted cosine similarity as the performance index of the generalized curve. The cosine similarity is optimized to get the scaling factor. Then, by adding the acceleration coupling term to the original DMP, trajectory planning and force control are achieved on the curved surface. Finally, some simulations and experiments demonstrate the performance of our proposed method.
Severe Patients Shock Detection Model Based on Convolutional Neural Networks

Medical research has shown that the prolongation of Capillary Refilling Time (CRT) is significantly associated with the shock caused by various pathogenesis, and the shock detected in critically ill patients as earlier as possible has important clinical significance. Utilizing capillary refill time measuring instruments, we can implement standardized and mechanized measurement of CRT, and get stable and reliable photoplethysmogram (PPG) raw signal data of CRT. However, there are many challenges in extracting clinical parameters from PPG raw signal data and analyzing the shock occurs or not depending on these parameters, such as great affection by noise, poor ability to cope with variations, and underutilization of raw data. To cope with these challenges, we propose an end-to-end shock detection model based on Convolutional Neural Networks (CNNs). In this paper, the convolutional kernel of dense neural network and mathematical network are proposed innovatively. Our shock detection model achieves 0.89 F1-Score using clinical CRT data, which can provide direct and exact medical verdict indicating the patient be in shock or not, which has clinical value.
A Novel Triple-Mode Wideband Slotline Antenna

In this paper, a novel triple-mode planar wideband sloltine antenna is presented. The proposed antenna starts from a traditional slot one, which only has a radiation mode and suffers from intrinsic narrow bandwidth. To deal with this problem, two pairs of short-ended slots are symmetrically etched along the traditional slot one near the maximum electrical field of its full-wave radiation mode. After suitably choosing the locations and parameters of the short-ended slots, extra two radiation modes can be introduced and merged with the full-wave one, resulting in a wideband characteristic with three resonances. To validate this, a triple-mode prototype is designed and experimentally measured. The experimental results agree well with the theoretical analysis and simulated ones verifying a simple designing approach of wideband slotline antennas with three radiation modes.
Implementation of a Remote Center of Motion Robot Finger with Tactile Sensors in the Joints

Robot grippers and hands are commonly used to grasp various objects. However, for multi-link fingers, it is challenging to cover the joints with tactile sensors, which limits the safety and sensitivity of such fingers. In the current paper we use a remote center of motion (RCM) mechanism for the joints, which enables us to cover also the joints completely with soft and thick tactile sensors, in particular distributed 3-axis sensors. The RCM joints are implemented as 6-bars, and we evaluate their robustness in simulation. A real implementation of the gripper is tested by grasping various objects, and the resulting tactile sensor readings are presented.
Research on Impedance Control of Flexible Joint Space Manipulator On-Orbit Servicing

In this paper, the positional accuracy and contact force index requirements of the manipulator are analyzed according to the tolerance index of the space manipulator screwing. An position-based in Cartesian space impedance control strategy based on friction identification and compensation is proposed. By using joint friction torque compensation to improve the system control precision and setting the desired Cartesian position of the manipulator end point to control the contact force, this strategy solves the contradiction between the positional accuracy index and the contact force index requirement of manipulator during contact operating. The control algorithm is designed based on the system dynamics model, and the stability analysis of the control algorithm is given. The correctness of the control strategy is verified by simulation and on-orbit implementation. China's space manipulator has successfully completed the actual on-orbit servicing mission based on impedance control for the first time.
Three-Dimensional Truss Modelling for Biped Climbing Robots

Recognizing and modelling the three-dimensional (3D) truss-style environment, consisting of cylinder members, is a challenging task for climbing robots. State-of-the-art segmentation algorithms always suffer from incomplete member-segmentation. To solve this problem, in this paper we propose a truss environment modelling (TEM) method using a sliding bounding box algorithm. TEM can obtain accurate poses of the members in truss environments by two strategies. First, the remaining incomplete segmented members are localized by a sliding bounding box along the axis of the members. After that, members are merged based on the new endpoints detected after projecting points in the new bounding box onto the axis, reducing the uncertainty and complexity of members merging. Our proposed method was verified by experiments with steady performance, which satisfied the requirements of the climbing robots.
Hierarchical Stochastic Optimization With Application to Parameter Tuning for Electronically Controlled Transmissions

In mechanical systems, control parameters are often manually tuned by an expert through trial and error, which is labor-intensive and time-consuming. In addition, the difficulty of this problem is that there often exist multiple solutions that provide high returns. As a designed objective function is often not optimal in practice, the solution that provides the highest return may not be the optimal solution. Therefore, it is often necessary to verify the multiple candidates of the solution to identify the one most suitable for the actual system. To address this issue, we propose a parameter optimization system using hierarchical stochastic optimization (HSO) that can handle multimodal objective functions. In a case study of electronically controlled transmissions, the optimizer learns multiple sets of parameters that satisfy all constraints and outperforms the parameters manually designed by human engineers. We demonstrate experimentally that our HSO can identify several modes of the objective function and is more sample-efficient than the existing methods, such as cross-entropy method and covariance matrix adaptation evolution strategy, as well as a human engineer.
A Waveform Display Synchronization Method in Multi-channel Digital Three-Dimensional Oscilloscope

As the signal frequency increases, the signal timing margin decreases sharply. Moreover, some accidental signals should be captured for circuit debugging. Thus, highperformance measuring instruments are urgently needed. A digital oscilloscope is the most commonly used time-domain test instrument. On one hand, the capture capability of oscilloscope depends on its signal processing speed and waveform display method. The processing speed of traditional digital oscilloscope is slow because of its serial process method. The sample data storage is stopped when sample data are processed. If an accidental signal occurs at this moment, it cannot be captured. Therefore, the process time is named dead time. To reduce dead time, digital three-dimensional oscilloscope (DTO), which owns fast signal processing capability and three-dimensional waveform display effect, is proposed. On the other hand, DTO is a multi-channel acquisition system. The timing difference of data storage and waveform processing in the multi-channel system appears. It leads to extra delay between different channels. It is called multi-channel synchronization problem. In this paper, the mathematical model of acquisition and display system in multichannel DTO is constructed. Furthermore, the synchronization problem in the proposed low cost multi-channel DTO is researched. The synchronization method is proposed and validated. The result shows that the extra delay between different channels is eliminated. The proposed multi-channel DTO can help engineers capture accidental signals more easily.
A 900-MHz 1.25-dB Noise-Figure Differential-Output LNA with 12.5 dB/mW FoM

A 900 MHz LNA with balanced output and 12.5-dB/mW figure-of-merit (FoM) is presented. The architecture exploits the benefits of both inductive degeneration and noise cancellation which helps in achieving the optimum noise figure (NF). The LNA has a wideband gain and input matching is achieved using an off-chip inductor. Inductive degeneration and quality factor (Q) of the input matching network improves the NF of the LNA (with wideband gain) at a spot frequency. The transconductance of the core-LNA is fixed by a constant-gm circuit. Simulation results show that the LNA has a minimum NF of 1.25 dB at 900 MHz, transmission gain (S21) of 33 dB, S11 of −19 dB at 900 MHz, IIP2 of +2 dBm, and IIP3 of −15 dBm. The LNA, designed in 180 nm CMOS, consumes 4.4 mA from a 1.8 V supply and has a negligible differential-gain error of 0.138 dB, at the input matched frequency. A 2.5-dB NF balanced passive mixer on top of the LNA is also implemented.
Haptic and Visual Enhance-based Motor Imagery BCI for Rehabilitation Lower-Limb Exoskeleton

The motor imagery (MI) based on electroencephalogram (EEG) via non-invasive Brain Computer Interface (BCI) is a promising interactive method to provide effective communication between the disabled and rehabilitation robotic device. Interactive efficiency of MI-based BCI largely relies on the performance of subject’s motor imagery. In this work, we proposed a simple and effective paradigm based on visual and haptic modalities for a high-quality initialized and calibrated MI-BCI model. Five healthy male subjects participated in motor imagery experiments with two paradigms. The proposed paradigm utilized mixed cues based on the visual and haptic modalities where the haptic cues were provided by the mini vibration motors, and a traditional paradigm utilized the ordinary arrow visual cues. The analysis of the topographic maps was conducted to illustrate the differences of the EEG in both paradigms. The average classification accuracy of motor imagery in the proposed paradigm improved about 14% compared to the traditional paradigm. Furthermore, a subject completed the qualitative verification experiment of the trained model on a rehabilitation lower-limb exoskeleton which proved the feasibility of the proposed paradigm.
An Overview of Cognitive Radar: Past, Present, and Future

Modern radar systems face numerous challenges due to requirements of robust, high performance across multiple missions and multiple functions in the face of dynamically changing environments. Cognitive radar has emerged over the past 15 years through synergy of cybernetics, waveform diversity, and knowledge-aided signal processing as a new vision for the future of radar systems that can address these challenges. This article provides an overview of the historical context and mechanisms for cognitive processing in engineering systems, which have driven an evolution in the definition, analysis, and design of cognitive radar. A survey of cognitive radar research trends is given to provide insight on applications and techniques, while technical and practical challenges to future progress are discussed.
Design, Fabrication and Morphing Mechanism of Soft Fins and Arms of a Squid-like Aquatic-aerial Vehicle with Morphology Tradeoff

Some animals have the ability to shuttle freely between water and air. These creatures have evolved special body structures to accommodate both underwater and airborne environments. Natural creatures have given us great inspiration to the variable structure design for aquatic-aerial multimodal vehicle. In this paper, we propose a new squid-like soft morphing fins according to the flying squid. This squid-like soft morphing fins can spread and fold for the adaptation of the aquatic-aerial multimodal locomotion. When the fin is spread, it can generate lift force for the aquatic-aerial vehicle. When the soft fin is folded, it can reduce the drag force during the underwater movement. An unique air cavity inside the fin was designed as actuator to bend the soft fin. The fabrication method of the soft fin was introduced. The bending performance of the soft fin was analyzed by FEA simulation and tested by several experiments. Then, morphology tradeoff strategy of aquatic-aerial vehicle with soft morphing fins was investigated by the wind and water tunnel. The results demonstrate the soft morphing fins have fast actuating response and good deformability, which verifies the soft fin can help the aquatic-aerial vehicle to realize multi-modal locomotion.
Synergistic Optimization based Binaural Time-Frequency Masking for Speech Source Localization

Monaural time-frequency (TF) masking has been demonstrated to advance the performance of binaural speech source localization. However, it fails to consider interaural information, which may result in severe distortion of interaural cues. To mitigate these impacts, this paper presents a novel method for binaural speech source localization based on binaural TF masking. Firstly, the CNN-based binaural TF masking network is designed to suppress the noise and reverberation in TF fragments, which is trained in the independent stage. Then, the resulted binaural TF masking is synergistically refined with the localization network to compensate for the distorted interaural cues. The final source direction is estimated using the trained network. The proposed method is compared with other baseline methods and two-stage models composed by cascade TF masking network and localization network. Experimental results show our method outperforms the other compared methods in the adverse environments with different reverberation time and signal-to-noise ratios.
DMSSM: A Decision-Making Scheme of Switch Migration for SDN Control Plane

In SDN, every controller of the distributed control plane manages a set of switches. Each switch set forms an independent topology domain. Switch migration is a promising approach for the load balancing of control plane, which would change the topology domain after migrating switches. However, it would require more controllers to process the control signaling, if the topology domain became graphically disconnected after migration. As a result, it would increase the transmission and processing delay of control signaling. Reducing the transmission and processing delay of control signaling remains a problem to be solved. In this paper, we proposed a decision-making scheme of switch migration (DMSSM) for SDN control plane. Firstly, at the preparation phase, we ensure the connectivity of migrate-in domain and migrate-out domain. For the migrate-out domain, controller generates a migration switch set. Switches in this set are the non-cut vertexes of the topology graph. For the migrate-in domain, controller would select one from the set, and the selected switch has at least one edge connected to the migrate-in domain. At the decision phase, the migration benefit model is proposed to solve the migration decision problem. The migration benefit model is built to make a tradeoff between the transmission delay of control signaling and the load balancing rate of controllers. The simulations demonstrate that DMSSM can reduce the average transmission delay of signaling by 17% and reduce the processing delay by 22.7%.