Abstract:Ocean buoys generate six degrees of freedom motion due to the influence of marine dynamic environment, which can affect the reliable operation of observation platform and instruments, and even lead to measurement results errors, affecting the safety and data quality of ocean buoys. Therefore, the accurate measurement of buoy motion is of great practical significance. This article establishes a hardware system by integrating a micro inertial measurement unit with a global navigation satellite system to obtain buoy motion-related data. A carrier phase smoothing filter model is used for data preprocessing, and a least squares redundancy algorithm is fused to calculate the buoy attitude data, obtaining high-precision dynamic buoy attitude. After comparing the results of a swaying platform simulation of motion, the root mean square error of attitude angle is less than 0. 5°, and the root mean square error of horizontal velocity is less than 0. 05 m/ s. Additionally, through practical sea trials experiments, especially during the passage of a typhoon, the test results show that the system works stably and reliably without divergence phenomenon, with over 95% overall valid data.

Abstract:The turbine tip clearance measurement has problems of poor stability, easy interference and low accuracy at high speed of aeroengine in harsh environments such as high temperature. To address these issues, a dynamic synchronous measurement method of turbine blade speed and tip clearance based on the principle of laser self-mixing is proposed. Firstly, a self-hybrid interference model based on the three-mirror F-P cavity model is proposed, and a mathematical model of velocimetry and ranging is formulated on this basis. Then, the processing of dynamic self-mixing interference signals under the rotation of turbine blades is studied, and the collected signals are successively processed by bandpass filtering and wavelet noise reduction. FFT is used to obtain the frequency and the blade tip clearance value. After that, static and dynamic laser self-hybrid interferometric ranging experiments are implemented for verification. Finally, the error sources affecting dynamic measurement are discussed, and the measurement system and algorithm are optimized and compensated. Experimental results show that this method can effectively improve the stability and accuracy of synchronous measurement of turbine blade speed and tip clearance. The relative error of speed measurement is 1% , and the error of tip clearance measurement is 23 μm.

Abstract:The protrusion of angular contact ball bearings is the distance of the same end face of the inner and outer rings under the axial preload, which is the basis for pairing precision angular contact ball bearing. To realize the rapid and precise measurement of the protrusion, an optical precision measurement method is proposed and a measuring device is developed. By replacing the bearing positioning claws of different sizes, the protrusion amount of the 7208C, 7208AC, 7308B, and 7408B bearings can be measured. The Hertz contact between bearing ring and roller is analyzed, and the relationship between bearing protrusion and axial load is revealed. The change trend of the bearing protrusion slows down as the axial load increases, and gradually tends to linear correlation. Based on the finite element method, the deformation analysis and simple harmonic vibration analysis of the frame and inner ring drive of the measuring device are carried out. The vibration amplitude of the sensor probe is reduced to 0. 029 μm after optimization. The 7008C (P2) angular contact ball bearings protrusion is measured. The verification results show that the measurement accuracy reaches 0. 5 μm, and the measurement deviation of the sample is less than 0. 2 μm.

Abstract:Shape from focus is a commonly-used method for measuring the three-dimensional topography of components with small size. However, the measurement accuracy is often affected by noise in the focus evaluation curve. Additionally, the efficiency is limited by both the number of image sequences and the focus evaluation algorithm. In this paper, an adaptive weighted focus extreme search method combining the theory of dual-fitting optimization and a focus unimodality evaluation index is proposed. Furthermore, a cubic polynomial quadratic interpolation algorithm is used for interpolation, and the depth information is optimized by a multi-level median blend filtering algorithm. Experimental results show that the proposed method reduces the RMSE of simulated image data by 19. 08% and 17. 32% compared to Gaussian fitting and polynomial fitting, and maintains three-dimensional resolution in regions with significant noise interference. At the same time, we also measured the drill bits. Results show that the proposed method reduces the RMSE by 77. 8% and 62. 6% even when the number of image sequences and image resolution are reduced by 50% , which effectively reduces the influence of measurement curve noise on measurement results and improves measurement efficiency.

Abstract:Considering that the eccentricity error in the process of measuring the focal length of spherical lens results in the uncoincident measured optical axis relative to the actual axis of lens, a high-precision measurement method of laser differential confocal length based on eccentric suppression is proposed, where the size and direction of the lens′ center deviation are measured by rotating the table to realize the error acquisition of measured lens. By analyzing the error value and direction driving attitude adjustment motor, the influence of eccentricity error on the accuracy of focal length measurement is eliminated during the measurement process. By constructing the system and optimizing the system parameters, the high-precision measurement of laser differential confocal length is realized. Finally, the high-precision measurement of focal length based on eccentricity suppression is realized, which solves the problem that the measurement results are affected by the uncoincident measured optical axis relative to the actual axis of the lens during focal length measurement. Based on this system, the focal length measurement experiment results show that the relative repeatability measurement accuracy (RMS) can reach 0. 000 503% when the focal length is measured with a 100 mm lens. This method significantly improves the accuracy of focal length measurement and repeated measurement accuracy, which provides an effective way for precision measurement of focal length. At the same time, this method can be utilized for the processing and assembly of the lens group to improve the imaging quality and measurement accuracy of the lens group.

Abstract:Vibration has a great impact on the accuracy of both instruments and machine tools, and its accurate detection and analysis is a prerequisite for effective vibration control. In this study, a high sensitivity and low coupling 3D elastic mechanism, and its parameter optimization method are proposed. The configuration of the 3D elastic mechanism is introduced, and the design of the 3D elastic mechanism is completed through theoretical modeling, parameter optimization, and simulation analysis. Finally, the elastic mechanism is combined with a high-sensitivity and low-coupling sensing system to develop a 3D low-frequency accelerometer system with high performance, and the performance of the accelerometer are tested through experiments. According to the experimental results, the sensitivity of the 3D accelerometer using this elastic mechanism is better than 2. 0 V/ (m·s -2 ), the coupling error is lower than 1. 5% , as well as the frequency response range is 1 ~ 13 Hz, which is in accordance with the design requirements. Therefore, the 3D elastic mechanism proposed in this study is characterized by 3D equal sensitivity and low coupling, and can be widely used in various 3D accelerometers.

Abstract:As a calibration-grade instrument, the 7. 5-digit multimeter can be used for the calibration of sensor electrical parameters in the aerospace field. The basic problem of the DC amplifier directly affects the measurement accuracy of the multimeter. In this article, a low DC bias amplifier is designed, with a common-source common-base amplification circuit composed of JFET, a proportional buffer current mirror, a V-I conversion constant current source circuit as the input stage amplification circuit, and a cascaded high-gain operational amplifier to form a voltage series negative feedback structure to solve the contradiction between high input impedance and low noise amplification. The DC bias model consisted of offset voltage and temperature drift is analyzed. It is found that the offset voltage of the current mirror compensates for the offset voltage of the JFET, and the resistor repair circuit is optimized to improve the offset voltage of the JFET. Temperature drift simulation shows that the current temperature drift of the V-I conversion current source and the proportional resistance temperature drift are two main factors of amplifier temperature drift. The overall temperature coefficient of the system is improved through the selection of low-temperature drift sensitive devices, the optimization of PCB thermal layout, and the design of windproof shells. Experiments show that the absolute value of the offset voltage of this amplifier is less than 11 μV, which is better than that of the JFET precision amplifier OPA828. The amplifier temperature coefficient is -2~ -4 μV/ ℃ , which is in the same grade as the Keysight 3458A temperature coefficient without temperature calibration. The amplifier meets the design requirements of the 7. 5-digit multimeter.

Abstract:Bio-inspired Flapping-Wing Flying Robot (FWFR) mimicking the flight mechanism of animals like birds and insects in nature has the advantages of high safety and good disorientation, which has extremely significant application prospects in disaster rescue, antiriot and other aspects. In order to realize autonomous flight and perform detection tasks in unknown complex environments, a navigation system integrating functional modules such as perception and mapping, planning and obstacle avoidance, and flight control guidance, etc. need to be developed. This paper firstly gives an overview of the FWFR′s navigation system by classifying the robot into two categories of micro and medium-large according to the wingspan size, and then compares and analyzes the main research progresses in the navigation system of both FWFRs at home and abroad. Then, the key technologies involved in autonomous navigation systems such as perceptual localization and mapping, planning and obstacle avoidance, trajectory tracking and flight control guidance, etc. are analyzed and reviewed, the limitations and urgent problems are also pointed out. Finally, an outlook on future research trends is provided, including enhancing onboard embedded computing capabilities, multi-modal information fusion, multi-modal flight flow field perception, research of biomimetic vision systems, and swarm perception and formation control etc.

Abstract:Soft robotic arms have been widely used in various fields such as biomedical and marine exploration in recent years due to their advantages of multiple degrees of freedom, high flexibility, strong environmental adaptability, and high safety and interactivity. The soft robotic arm is made of highly deformable flexible materials. Due to the nonlinear characteristics of its materials, the precise control of the soft robotic arm has always been a research focus and difficulty in this field. Domestic and foreign researchers have carried out extensive research on the control methods of the soft robotic arm and made significant progress. However, there are still several issues that need to be addressed urgently. Therefore, this article summarizes the research achievements of domestic and foreign researchers in the motion control methods of soft robotic arms in the past decade. The commonly used control methods and the latest technologies of soft robotic arms are analyzed and summarized. The difficulties and challenges faced by soft robotic arm control are pointed out. The future development direction of soft robotic arm control methods is explored and prospected.

Abstract:To address the problem that the orthopedic force of the traditional bone external fixator cannot be accurately controlled and has poor safety, the article establishes a knee bone external fixation robot based on the RCM configuration and proposes an orthopedic force tracking control method with indirect adaptive impedance. Due to the existence of mechanical friction and external uncertainty, to address the problem of poor robustness of impedance control, the force error signal is adopted as the driving force of the target impedance, a new impedance model is formulated to adapt to the changes in the orthopedic environment. According to the changes in the contact force, the adaptive law is designed to regulate the impedance parameters in real time, which compensates for the uncertainty of the environmental dynamics on the line. Therefore, the system′s force tracking error is zero. Comparative simulations and prototype experiments of the proposed control algorithm for tibial orthopedic force control are implemented. The results show that the impedance control simulation results of the weighted average of the performance indicators are 2. 12, 8. 58 and 13. 2, and the maximum error of the force tracking experiment is 20 N. Compared with impedance control, the weighted average of the performance indicators of adaptive impedance control simulation is only 0. 36, 0. 18 and 0. 61, and the force tracking fluctuation error is controlled to be within ±3N, which has better robust and adaptive ability.

Abstract:Aimed at the characteristics of the ankle joint like quick-change-of-angle and multi-degree-of-freedom, we propose an active booster exoskeleton based on a multi-branch spatial linkage mechanism to assist the movement of ankle joint. The exoskeleton is driven by motor combined with a spatial linkage mechanism to achieve the active dorsiflexion / plantar flexion and adduction / abduction motion of the ankle joint for the purpose of locomotion assistance. The corresponding aim is to improve the coordination of ankle exoskeleton movement following and reduce the restricted freedom of movement on the wearer. Furthermore, gait recognition based on foot force measurement system and hierarchical control strategy using a motor state machine for ankle-assisted exoskeletons have been studied. The ankle joint was tested and assisted in the evaluation. The test results show that the effective power range of the ankle exoskeleton (plantar flexion 30° ~ dorsiflexion 20°, adduction 35° ~ abduction 15°) can meet the needs of normal walking with the good motion following (Angle error ≤2°) for the exoskeleton and the significantly attenuated lower leg EMG of the subjects by 28. 91% , which can provide effective power.

Abstract:To address the issue of poor tracking performance in locomotion tasks of hexapod robots under variable time delay conditions, this article proposes a bilateral teleoperation control method based on a wave impedance online compensation strategy. The strategy is built upon a four-channel control architecture and incorporates a delay estimator to predict communication delays. It further designs online adjustment rules for wave impedance to improve the system′s tracking performance. Additionally, the time-domain passivity control method is combined to provide a secondary compensation for potential activeness in the communication link and the environmental side, which could ensure the system′s absolute passivity. The control law parameters for the master and slave ends are designed by using the Llewellyn criterion. The proposed method is evaluated through the construction of a semi-physical simulation experimental platform and a physical experimental platform based on Vortex. Experimental results show that variable wave impedance control combined with time domain passivity control can ensure the passivity of the system. Compared with traditional bilateral teleoperation, the speed tracking performance is improved by 84. 3% , and the force fluctuation range is reduced by 84. 7% .

Abstract:Point cloud is the most commonly used form of 3D data processing in the fields of autonomous driving, robotics, remote sensing, augmented reality ( AR) , virtual reality ( VR) , electric power, architecture, etc. Deep learning methods can not only handle large-scale data, but also extract features independently. Therefore, point cloud deep learning methods have gradually become a research hotspot. This article reviews the research progress of 3D point cloud analysis methods based on deep learning in the past decade. Firstly, the relevant concepts of deep learning for 3D point cloud are presented. Then, for the four tasks of point cloud object detection and tracking, classification and segmentation, registration and matching, and stitching, the principles of the corresponding deep learning methods are elaborated. Their advantages and disadvantages are analyzed and compared. Next, eighteen kinds of point cloud datasets and performance evaluation indexes for four types of point cloud analysis tasks are introduced. The performance comparison results are given. Finally, the existing problems of point cloud analysis methods are pointed out, and the further research work is prospected.

Abstract:This article proposes a new method for continuous advanced detection and imaging of abnormal body during excavation. The problem of poor accuracy in single imaging with fixed field sources is effectively addressed. It provides strong support for parallel operation of tunnel excavation and forward detection. Firstly, a theoretical model for continuous advanced detection and imaging of abnormal body during excavation is formulated. Then, the imaging effect and accuracy improvement methods for abnormal body identification are studied. On the basis of effectively identifying the geometric shape of the abnormal body ahead, the mean square error of conductivity is reduced from 0. 273 to 0. 156 by increasing the excavation mileage, from 0. 173 to 0. 153 by increasing the potential sampling frequency, and from 0. 183 to 0. 167 by increasing the number of potential measurement points. The imaging accuracy is gradually increased. Finally, the imaging effect of anomalies with different types and shapes in front of the field source during excavation is analyzed. A mud trough experimental system is established, and comparative experiments on imaging effects are carried out. The effectiveness of this method is evaluated.

Abstract:The existing methods for segmenting CT images of castings with weak edges have problems of difficulty, low precision and poor robustness. To address these issues, this article proposes a U-shaped network segmentation algorithm that fuses residual module and mixed attention mechanism. Firstly, the algorithm is based on U-Net. The deep residual networks ( ResNets) is established as the backbone of the network to solve the inadequate feature extraction capability of the original U-Net. Then, the improved hybrid attention mechanism is introduced, and it characterize the target region and the channel to improve the network sensitivity. Finally, a new loss function (FD loss) combining Focal loss and Dice loss is used to mitigate the negative effects of sample imbalance. The performance of the algorithm is evaluated by using the 120 valve body dataset. The experimental results show that the pixel accuracy ( PA) and intersection over union (IoU) of the proposed algorithm for casting segmentation reach 98. 72% and 97. 40% , which are better than the those of the original U-Net and other mainstream semantic segmentation algorithms. This work provides a new idea for the weak edge segmentation problem.

Abstract:Autonomous underwater vehicles (AUVs) equipped with visual detection systems are capable to detect underwater artifacts, which is of great significance to deep-sea archaeology. Underwater cultural artifacts are situated within a dynamic and intricate environment, where the target objects are often fragmented, layered and concealed under sediment. These conditions pose significant challenges to the effective extraction of discernible features, thereby impeding the capability of AUV for reliable and accurate detection of underwater artifacts. In order to solve these problems, this paper proposes an underwater cultural artifact detection algorithm based on the deformable deep aggregation network model. To fully extract the target feature information of underwater cultural artifact in complex environments, this paper designs a multi-scale deep aggregation network with deformable convolutional layers. Besides, the SimAM attention module is designed for the feature optimization, which enhances the potential feature information of cultural artifact target and weakens the background interference information simultaneously. Finally, the prediction of cultural artifact is achieved through fusing feature at different scales. The proposed algorithm has been extensively validated and analyzed on the collected underwater artifact datasets, and the precision, recall, and mAP of algorithm are 92. 7% , 90. 5% , and 92. 2% , respectively. Additionally, the proposed algorithm has been deployed to the AUV system, specifically the artifact detection frame rate of visual detection system reaches 19 fps in the actual deep-sea test scenario and this can satisfy the real-time detection task.

Abstract:To provide high-precision data standards for the positioning accuracy and anti-interference ability of indoor positioning technology, a position and attitude measurement method of the spatially moving target in monocular vision is proposed. The machine vision projection matrix solution and photogrammetry resection technology are combined to achieve the solution of camera exterior parameters through a target in any position and attitude. First, the real camera station is calculated through the ground control field target world coordinates and image coordinates. Then, the virtual camera station is solved based on the target initial world coordinates and realtime image coordinates. Finally, according to the virtual and real camera station exterior parameters, the initial world coordinates of the target are transformed into the real-time world coordinates of the target. The experimental results show that, in the measurement space of 10 m×4. 5 m×3. 8 m, the root mean squared error (RMSE) of target displacement distance measurement is 0. 358 3 mm in X direction, 0. 350 9 mm in Y direction, and 1. 475 2 mm in Z direction. The attitude angle measurement RMSE is 0. 094 0° in φ, 0. 089 3° in ω, and 0. 025 4° in κ. This method can meet the needs of high-precision real-time positioning and attitude determination of moving targets in a large range. Keywords:spatial

Abstract:Existing multi-object tracking algorithms make insufficient use of appearance and geometric information, and the information exchange among adjacent regions of the tracked object is limited. To solve this problem, a multi-object tracking algorithm based on multi-stage association is proposed, which applies geometric and appearance information to different association stages according to the different association states among objects. Firstly, a fast matching module based on the regularized distance intersection and union ratio (DIoU-Mea) is employed to efficiently handle the matching task of strongly correlated objects only using geometric information. Secondly, an association module based on the sparse graph network (GNN) is incorporated to model the neighborhood of the tracked object, facilitate information exchange among objects, and improve tracking accuracy. Finally, a double verify module (Double-Revise) is introduced, which utilizes the channel attention fusion feature model and the shape intersection and union ratio to further refine the tracking results. By utilizing the complementary advantages of different stage matching algorithms and making reasonable use of appearance and geometric information in each stage, the proposed algorithm effectively filters out incorrect matches and accurately identifies the correct object correspondence. The proposed algorithm is evaluated and tested on the MOT17 dataset. Its high-order tracking accuracy (HOTA) reaches 64. 8% on the test set. Results show its good performance and robustness in dense scenarios.

Abstract:To address the issue of sample imbalance in EEG obtained through rapid serial visual presentation (RSVP), a multi-task learning model for EEG classification is proposed. Firstly, a deep shared feature extraction module is established, which utilizes a convolutional neural network to automatically learn shared parameters and extract depth-related features associated with tasks. Then, a multi-task objective function is constructed based on the classification task and hyper-sphere constraint task, utilizing the joint learning of these two tasks to extract more effective discriminative features and improving the model′s generalization performance. Experiments are implemented on a public RSVP EEG dataset. Compared with commonly used EEG classification models such as DeepConvNet, EEGInception, DRL, and EEGNet, the proposed model named Multi-task EEGNet can achieve the average AUC improvement of 3. 57% , 1. 84% , 6. 22% , and 2. 09% respectively, across 32 subjects. The results indicate that the proposed multi-task learning model can extract discriminative features more fully, effectively improve model classification performance, and better solve the sample imbalance problem in EEG classification tasks.

Abstract:Due to the small size and high background interference of microaneurysms in retinal images, traditional methods have low detection accuracy. Currently, deep learning models mostly focus on detecting large-sized targets, which have complex structures and poor detection performance for small targets. To address these issues, a micro aneurysm detection method based on parallel multi-scale convolutional neural networks is proposed. Firstly, a corresponding relationship between the size of microaneurysms and the theoretical receptive field used for detection is established. Then, a parallel convolutional network consisted of two receptive field scales is constructed, which is based on the type and size range of microaneurysms. Finally, a training set construction and data augmentation method based on active learning is proposed to improve the detection performance of the model. The method is compared on two public datasets and one self-collected fundus dataset. The experimental results show that the method can effectively detect microaneurysms, and has better detection performance compared to similar methods for small and vascular adherent microaneurysms.

Abstract:Due to deformability, flexible eddy current sensors are used in nondestructive testing for complex structures. The flexible Koch fractal eddy current sensor consistently detects short cracks in all directions due to the eddy current conditioning effect of its local microstructure. However, the detection of near-surface and internal cracks has not been studied. This article formulates the equivalent circuit model of the difference pick-up sensor. The evolution of eddy current distribution with depth is studied by simulation method. Through the experimental method, the detection effect of the sensor on the prefabricated crack specimen covered with different thicknesses of aluminum plate is studied. The finite element results show that, with the increase of depth, the eddy current density decreases, the concentration decreases, and the distribution pattern is more and more different from that on the surface. The eddy current shape changes from snowflake to circular. The experimental results show that the output signal of the sensor decreases with the increase of the thickness of the covering layer. When the excitation frequency is 10 kHz, the sensor can detect the maximum thickness of the covered aluminum plate when the crack is 2. 0 mm.

Abstract:Due to the remarkable technical advantages, magnetic flux leakage testing (MFL) is widely used in nondestructive testing of ferromagnetic components, especially in the field of internal inspection of oil and gas pipelines. The spatial resolution of MFL inspection is determined by the sensor arrangement density. However, the sensor arrangement density is limited by its size, especially for single-row sensors. Therefore, to improve the spatial resolution for the inspection, the multi-row and staggered arrangement of sensors is a simple and feasible method. Due to the different background magnetic fields at the positions of multiple rows of sensors, the influence law of different background magnetic fields on the detection signal is not clear. Therefore, it is necessary to carry out a theoretical analysis of the above problems. A method is proposed to correct the detection data of multiple rows of sensors. Based on the magnetic charge theory, the defect detection signal is divided into the superposition of the background magnetic field and the defect leakage magnetic field, and the superposition rule of the two is given. Based on this, the method of correcting the detection data of multiple rows of sensors is proposed. The effectiveness of the proposed method is evaluated by COMSOL simulation and experimental results.

Abstract:Wing is one of the key components of aircraft. On-line monitoring of wing deformation during flight is helpful to improve the safety and mission performance of the aircraft. Therefore, a dynamic wing deformation monitoring system based on the fiber Bragg grating sensor technology is proposed in this article. The relationship between wavelength variation of FBG and wing surface curvature is analyzed theoretically. The strain compensation is realized by the temperature sensor, and the serialization of discrete curvature is realized by cubic spline interpolation. Then, the deformation reconstruction algorithm based on continuous curvature is used to measure the wing deformation. 36 FBG strain sensors and 4 FBG temperature sensors are set on the wing surfaces of the CA42 aircraft. The ground static test results indicate that the measuring error of wing-tip deflection is 2. 5% . Finally, a flight test is carried out for the wing dynamic deformation measurement system. The strain, temperature and deformation data of the wing surface are recorded completely during the test process. The flight test results show that the wing tip deflection caused by the wing deformation is directly proportional to the vertical acceleration of the wing, and the coefficients are 86. 33 mm/ g (left wing) and 80. 04 mm/ g (right wing), respectively. The maximum deflection of the wing tip is 250 mm, which occurs when the normal overload is 2. 25 g. In addition, the smaller the radius of the aircraft maneuvering, the more the wing deforms. The dynamic wing deformation monitoring system shows good engineering adaptability.

Abstract:The influence of external factors from the environment (such as sample matrix, quenching agents, etc. ) and instruments can be reduced by the employment of ratiometric fluorescent probes to obtain more reliable detection results. In this article, two kinds of carbon dots (CDs) are synthesized and used as ratiometric fluorescent nanoprobes, which emit fluorescence at 440 nm and 570 nm, respectively, with 365 nm UV light excitation. The two kinds of CDs have opposite fluorescent responses to Cr (VI). The fluorescent probes are coated on the tip of the designed fiber tip with hydrogel to accomplish the online Cr ( VI) detection. The tooth-shaped structure on the fiber tip, which is processed by a femtosecond laser micromachining system, is beneficial to the excitation of fluorescent probes and the fluorescence collection of the sensor. A low-cost LED lamp is utilized as the excitation light source to save the cost and reduce the size of the sensor. The disadvantage of poor stability of the LED light is overcome due to the use of ratiometric fluorescent probes. In consequence, the miniature sensor realizes the self-correcting. It is proved that even though the intensity of the light source fluctuates greatly, the relative standard deviation (RSD) of 7 consecutive measurements is only 3. 1% . In the range of 0~ 200 μM, the sensor has a great linear relationship for Cr (VI) detection with a detection limit (LOD) of 0. 9 μM. The practicability and reliability of the sensor are demonstrated by the determination of Cr (VI) in real-world water samples.

Abstract:In navigation infrastructure-limited scenarios such as GNSS denied area, cooperative localization is an important approach to improve the localization accuracy. Self and relative localization are two main applications of cooperative localization. However, existing methods usually conduct self and relative localization separately, which not only limits the practical applications, but also leads to the performance loss by neglecting the motion correlations between swarm and individuals. To solve this problem, this work proposes a robust cooperative simultaneous self and relative localization (RC-SSRL) for collaborative swarm. It models the probability relationships among cooperative self-localization (CSL) and relative-localization (CRL) as well as cooperative measurements with a probability graph model, which depicts the probability relationship between relative-motion and self-motion. The marginal distributions in the graph models are calculated via the Gaussian belief propagation (GaBP), which is computationally efficient in message passing. Moreover, a Huber factor is designed based on the Huber loss function to implement the robust estimation by down-weighting the abnormal measurements in Gaussian message passing. Experimental results show that the proposed methods can estimate CSL and CRL states simultaneously, whose accuracy outperforms the traditional methods. Meanwhile, Huber factor can handle the abnormal measurements effectively to guarantee the system′s robustness. The proposed RC-SSRL provides a new way for the fusion framework of swarm coop`erative localization.

Abstract:It is difficult to solve the acoustic source localization problem of impact with the traditional methods since the propagation path of Lamb waves on the surface of porthole structure is no longer a linear path. To address this problem, a grid mapping probabilistic imaging localization method based on acoustic emission is proposed in this study. This method solves the nonlinear path problem of signal propagation by establishing a grid mapping model, and the corresponding theoretical time difference is obtained by calculating the fastest propagation path of signal at the grid nodes. Then the actual arrival time difference of signal is calculated by using the adaptive energy threshold method and the AIC method, and the probabilistic image is constructed by comparing the deviation of theoretical value with actual value to obtain the localization solution. The influence of band-hole structure on the propagation path of Lamb waves is analyzed by finite element simulation, and the basis of determining the signal propagation path is given. The feasibility of localization method is also verified by the localization experiments on 32 impact points, which provides an average absolute error of 1. 15 cm.

Abstract:The response time of magnetorheological fluid ( MRF) is a critical parameter that relates to the real-time controllability of magnetorheological smart actuators. However, the dynamic response of MRF involves a complex coupling from the circuit to the mechanical system, which requires addressing the challenge of decoupling from multiple parameters such as current, magnetic field strength, and shear stress. This article proposes a phase difference method based on the biased sine excitation current. By applying the biased sine current to excite sinusoidal magnetic flux density, the response time of MRF is obtained from the phase difference between the torque and the magnetic field, without facing the complex decoupling encountered in step response. In addition, this article breaks through the shear rate limitation of the general commercial rheometers through the design of the key mechanical parameters. It achieves MRF response time measurements at shear rates up to 3 000 s -1 . Based on this, this article designs and fabricates an MRF response time measurement device, and analyzes errors caused by eccentric assembly and magnetic field probe positioning. It is found that the response time of various samples is 23 ~ 140 ms under 1 ~ 3 A amplitude currents. In addition, the response time is first accelerated and then prolonged with the increase of sample concentration, which is negatively correlated with the external magnetic field strength.

Abstract:The radar echoes from weak pedestrians are easily submerged by strong background clutters in urban road traffic scenarios, resulting in the failure of trajectory tracking and prediction. To address this problem, this article proposes an integrated trajectory tracking and prediction method for weak pedestrians based on frequency-modulated continuous wave-multiple input multiple output millimeter wave radar. Firstly, the recursive Bayesian track-before-detect algorithm is utilized to directly extract target motion trajectory from the non-thresholding three-dimensional radar raw spectrum, which avoids the tracking performance degradation caused by the information loss from the traditional threshold-decision process. On this basis, this article proposes a Transformer-based end-to-end trajectory prediction model to further explore the spatiotemporal correlations of tracking trajectory and achieves accurate trajectory prediction of a weak pedestrian. Experimental results show that, when the signal-to-noise ratio is greater than - 20 dB, the average displacement error and final displacement error of the predicted trajectory of the proposed method are less than 0. 706 and 1. 215 m, respectively, which are all superior to traditional methods such as Gaussian process and long short-term memory network.

Abstract:High-precision positioning of underwater targets is an important prerequisite for unmanned surface vehicle (USV) to carry out tasks, such as seabed mapping, channel cleaning, and wreck salvage. However, the existing baseline positioning methods cannot accurately locate the targets in unknown waters. In practical tasks, USV needs to be equipped with side-scan sonar and supplemented by other means to determine the accurate position of underwater targets. In this article, aiming at the underwater target localization problem of the unmanned boat, we first model the underwater target localization process of side-scan sonar. Then, the influence of attitude error on underwater target positioning is analyzed, and the attitude error is eliminated by using an attitude correction matrix. Finally, the discrete Kalman filter algorithm is used to optimally estimate the multi-point measurement data and get the accurate position of the underwater target. The results of simulation experiments and USV integration tests show that the proposed method can effectively reduce the systematic errors in the measurement process and the average positioning accuracy reaches 0. 334 m

Abstract:A reconfigurable magnetic coupling underwater vectored thruster was designed to reduce the mechanical complexity, improve the waterproof sealing performance of micro underwater robot and ensure the flexibility of movement. Based on the non-contact magnetic coupled power transmission, the problem of waterproof between the motor and propeller was solved. Meanwhile, the reconfigurable mechanism was used to change the propeller position within two degrees of freedom, which realizes the reconfigurable vector propulsion of underwater vehicle. After establishing the magnetic field model of magnetic coupling, the correctness of magnetic field modeling was verified and the influence of reconfigurable mechanism on the magnetic torque of the magnetic coupling power transmission was analyzed by both ANSYS Maxwell magnetic field simulation and built magnetic torque measuring device. On this basis, the propeller thrust measurement device was fabricated, and the changes of rotational speed, thrust and correspondingly maximum vector thrust under different reconstruction angles were evaluated. The results show that the thruster can output the vectored force stably for the two degrees of freedom reconfigurable angles ranged between -15°and 15°.