Fast Positioning Research Articles

Multi-constellation and multi-frequency precise point positioning with fast ambiguity resolution on a global scale

To achieve global fast centimeter-level precise point positioning (PPP), ambiguity resolution (AR) is a prerequisite. We extended the PPP cascading AR method (PPP-CAR) to the GPS, Galileo, BDS-2, and BDS-3 all-frequency signals, in which more wide-lane (WL) ambiguities were fixed instantaneously to accelerate the narrow-lane (NL) AR. The performances of the multi-frequency PPP-CARs on a global scale were investigated in terms of the time to first fix (TTFF) of the NL ambiguities and convergence time (CT). The test results indicated that the TTFF and CT decreased significantly with increasing frequencies. The dual-frequency PPP-CAR achieved an average TTFF and CT of 9.4 and 7.8 min, respectively. The average TTFFs and CTs reached 7.6, 6.1, and 5.6 min, respectively, and 6.0, 4.4, and 4.3 min, respectively, for the triple-frequency, quad-frequency, and five-frequency PPP-CARs, with improvements of 19.1%, 35.1%, and 40.4%, respectively, and 23.1%, 43.6%, and 44.9%, respectively, compared to the dual-frequency PPP-CAR.

Angular error measurement of workpiece repositioning using a full-scale rotation detection method.

Workpiece repositioning error has always been a key factor affecting manufacturing accuracy. The issues become more sensitive when machining microstructures with special morphologies, where the declination error caused by the repositioning may lead to microstructural defects. To solve this practical problem, in this paper, we report the design of a fixture that can detect the plane angular displacement error between the workpiece and the tool, namely the Rotation Correction Fixture (RCF). The fiducial marker referred to as polar microstructure is proposed and placed on the RCF edge. Angular displacement measurement is realized by observing the microstructural changes. Simultaneously, a Full-scale Rotation Detection (FRD) method is proposed to obtain the full-scale and high-precision angular displacement, including coarse extraction based on Fourier transform and fine extraction based on the Fast and Robust Feature-based Positioning method. Template matching is employed to eliminate the phase ambiguity in the Fourier transform. The results show that the proposed method can realize the calibration of the workpiece declination with a standard deviation error of 250.24 seconds, which meets the needs of workpiece precision positioning well.

Fast position predictive control with current and speed limits for permanent magnet motor systems without weight coefficients

Fast position predictive control with current and speed limits for permanent magnet motor systems without weight coefficients

Integer Ambiguity Parameter Identification for Fast Satellite Positioning and Navigation Based on LAMBDA-GWO with Tikhonov Regularization

Satellite positioning is one of the main navigation technologies in unmanned aerial vehicles (UAVs), the accuracy of which has an important impact on the safety, stability, and flexibility of UAVs. The parameters of integer ambiguity are important factors affecting the accuracy of satellite positioning. However, the accuracy of the integer ambiguity cannot be guaranteed when only a few epoch data can be obtained in the fast positioning such that the identification matrix of the integer ambiguity parameters is seriously ill-conditioned and the information of position deviation is enlarged. In this paper, an error checking and correcting strategy is proposed, where a Least-square Ambiguity Decorrelation Adjustment-Grey Wolf Optimization (LAMBDA-GWO) Method combined with the Tikhonov regularization method is developed to improve the accuracy of integer ambiguity for fast satellite positioning. More specifically, the LAMBDA-GWO is first used to search the integer ambiguity parameters. To reduce the ill-condition of the integer ambiguity parameter identification matrix, the Tikhonov regularization method is introduced to regularize the identification matrix such that a reliable integer ambiguity floating-point solution can be obtained. Furthermore, the correctness of the integer ambiguity is checked according to the prior accuracy information of the initial coordinates and the Total Electron Content (TEC), and the part that fails the test is corrected by the Grey Wolf Optimization (GWO) Method. Finally, experimental studies based on a 522 m baseline and a 975 m baseline show that the identification success rates of the proposed method are both above 99%, which is 12% and 23% higher than that of traditional LAMBDA, respectively.

VMLH: Efficient Video Moment Location via Hashing

Video-moment location by query is a hot topic in video understanding. However, most of the existing methods ignore the importance of location efficiency in practical application scenarios; video and query sentences have to be fed into the network at the same time during the retrieval, which leads to low efficiency. To address this issue, in this study, we propose an efficient video moment location via hashing (VMLH). In the proposed method, query sentences and video clips are, respectively, converted into hash codes and hash code sets, in which the semantic similarity between query sentences and video clips is preserved. The location prediction network is designed to predict the corresponding timestamp according to the similarity among hash codes, and the videos do not need to be fed into the network during the process of retrieval and location. Furthermore, different from the existing methods, which require complex interactions and fusion between video and query sentences, the proposed VMLH method only needs a simple XOR operation among codes to locate the video moment with high efficiency. This paper lays the foundation for fast video clip positioning and makes it possible to apply large-scale video clip positioning in practice. The experimental results on two public datasets demonstrate the effectiveness of the method.

Vibration control of double pendulum type crane system with uncertainty in parameters by elimination of the natural frequency component

Overhead cranes are widely used to transport heavy loads, and their efficient operation requires fast and accurate positioning. However, residual vibration which prevents positioning accuracy generally tends to be induced by fast transportation. In previous paper, we proposed a control method which is based on the characteristic that the residual vibration is completely suppressed in a linear undamped system when excited by an external force which does not contain the natural frequency component of the system. To apply this characteristic to nonlinear damped systems, we defined the apparent external force which includes the influence of system nonlinearity and damping. It was confirmed that the residual vibration of a double pendulum type system model of crane can be suppressed by eliminating two natural frequency components from each the apparent external forces. In this paper, in addition, to improve the robustness for a double pendulum type system against the estimation error, new conditions are added to reduce the component around the natural frequencies from each of the two apparent external forces. The effectiveness of these conditions for robustness is verified through numerical simulations. Furthermore, changes in the robustness are examined when the position of the mass point near the support point of the double pendulum is changed. The results showed that the robustness can be improved in many cases except when the control time is short and the mass point is close to the support point.

Design and Modeling of 9 Degrees of Freedom Redundant Robotic Manipulator

In disaster areas, robot manipulators are used to rescue and clearance of sites. Because of the damaged area, they encounter disturbances like obstacles, and limited workspace to explore the area and to achieve the location of the victims. Increasing the degrees of freedom is required to boost the adaptability of manipulators to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. These robot manipulators offer a reliable way to handle the barrier challenges since they can search in places that humans can't reach. In this research paper, the 9-DOF robotic manipulator is designed, and an analytical model is developed to examine the system’s behavior in different scenarios. The kinematic and dynamic representation of the proposed model is analyzed to obtain the translation or rotation, and joint torques to achieve the expected position, velocity, and acceleration respectively. The number of degrees may be raised to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. The simulation of developed models is performed to ensure the adaptable movement of the manipulators working in distinct configurations and controlling their motion thoroughly and effectively. In the proposed configuration the joints can easily be moved to achieve the desired position of the end-effector and the results are satisfactory. The simulation results show that the redundant manipulator achieves the victim location with various configurations of the manipulator. Results reveal the effectiveness and efficacy of the proposed system.

A Lidar-Inertial Navigation System for UAVs in GNSS-Denied Environment with Spatial Grid Structures

With its fast and accurate position and attitude estimation, the feature-based lidar-inertial odometer is widely used for UAV navigation in GNSS-denied environments. However, the existing algorithms cannot accurately extract the required feature points in the spatial grid structure, resulting in reduced positioning accuracy. To solve this problem, we propose a lidar-inertial navigation system based on grid and shell features in the environment. In this paper, an algorithm for extracting features of the grid and shell is proposed. The extracted features are used to complete the pose (position and orientation) calculation based on the assumption of local collinearity and coplanarity. Compared with the existing lidar navigation system in practical application scenarios, the proposed navigation system can achieve fast and accurate pose estimation of UAV in a GNSS-denied environment full of spatial grid structures.

High-Performance Self-Powered Photodetector Based on the Lateral Photovoltaic Effect of All-Inorganic Perovskite CsPbBr3 Heterojunctions

CsPbBr3, an inorganic halide perovskite, has attracted great interest in recent years due to its excellent photoelectric properties. In this paper, we report a high-performance position-sensitive detector and laser communication sensor based on a CsPbBr3/4H-SiC heterojunction that effectively exploits the lateral photovoltaic (LPV) effect. The X-ray diffraction, X-ray photoelectron spectra, and photoluminescence data indicate that a high-quality CsPbBr3 film has been successfully obtained using pulsed laser deposition. The thickness of the CsPbBr3 film is shown to play a key role in the open-circuit voltage and linear LPV. A large position sensitivity (up to 827 mV/mm) of the LPV with a fast relaxation time is observed. Moreover, the shortest relaxation time of only 0.34 μs for 532 nm laser irradiation among counterparts is achieved in the detector under consideration. Furthermore, the position sensitivity and relaxation time of the LPV in the CsPbBr3/4H-SiC heterojunction show a weak dependence on the laser wavelength from 266 to 532 nm. The robust characteristics of fast relaxation time and high position sensitivity of the LPV make the CsPbBr3 junction a promising candidate for both laser communication sensors and self-powered high-performance position-sensitive detectors.

Performance research of real-time kinematic/5G combined positioning model

The global navigation satellite system provides real-time and all-weather positioning with high accuracy. Under a good observational environment, short-baseline real-time kinematic (RTK) can provide centimeter-level positioning results. However, RTK without model correction of ionospheric delay can significantly reduce the positioning accuracy, and cannot achieve fast and high-precision positioning when the baseline is too long or heavily occluded. Therefore, we propose a combined RTK/fifth-generation (5G) mobile communication technology positioning model by combining global positioning system-RTK with 5G time-of-arrival observations to improve the positioning accuracy under medium and long baselines. Experimental validation and analysis were conducted based on the measured data of different baseline lengths. The results revealed that the combined RTK/5G positioning model markedly improved the positioning performance in both static and dynamic modes under medium- and long-distance baselines. In particular, the RTK/5G model can also achieve good positioning results in conditions where some satellites are occluded. The combined RTK/5G positioning model is important for achieving high-accuracy, real-time, and continuous positioning in complex environments.

Adaptive Terminal Sliding Mode Control of Picking Manipulator Based on Uncertainty Estimation

In this paper, a robust nonsingular fast terminal sliding mode control scheme for the picking manipulator under the condition of load change and nonlinear friction disturbance is presented. Firstly, the dynamic equation of the picking manipulator under the condition of load change and nonlinear friction disturbance is established. Then, in order to avoid the singularity problem existing in the terminal sliding mode and improve the convergence time, a new nonsingular fast terminal sliding mode control strategy is adopted to design the control law of the picking manipulator, which can guarantee the finite time convergence. The adaptive law is used to estimate the uncertainties of the system, and the finite time convergence of the system state is proved by the Lyapunov criterion. In addition, the genetic algorithm is used to identify the friction parameters to realize the nonlinear friction compensation control of the system. Finally, the simulation results of the picking manipulator under different load conditions show that the controller designed in this paper realizes the fast and accurate positioning of the picking manipulator under load change and nonlinear friction, and the control strategy is reasonable and effective.

Kinematic coupling‐based trajectory planning for rotary crane system with double‐pendulum effects and output constraints

AbstractWhen the payload is too large or the hook mass cannot be ignored, the double‐pendulum phenomenon may happen in rotary cranes practical applications. The increase in dynamic complexity makes it more difficult to fast and accurate positioning while suppressing swing during cargo transportation. Moreover, output constraints should be considered in actual crane systems. In this paper, a novel kinematic coupling‐based trajectory planning method is proposed for double‐pendulum rotary cranes with the constraints on angular acceleration and velocity of the boom. The proposed trajectory consists of two parts: a positioning reference component and a swing‐eliminating component. The positioning reference trajectory takes into account the physical constraints of the actuator. The swing‐eliminating trajectory is designed based on the kinematic coupling relationship among the boom luffing, the hook swing and the payload swing. Lyapunov techniques and Barbalat lemma are used for stability analysis. Numerical simulation and real experiments verify the superior control performance and robustness of the proposed control method.

Fast and Interactive Positioning of Proteins within Membranes

(1) Background: We developed an algorithm to perform interactive molecular simulations (IMS) of protein alignment in membranes, allowing on-the-fly monitoring and manipulation of such molecular systems at various scales. (2) Methods: UnityMol, an advanced molecular visualization software; MDDriver, a socket for data communication; and BioSpring, a Spring network simulation engine, were extended to perform IMS. These components are designed to easily communicate with each other, adapt to other molecular simulation software, and provide a development framework for adding new interaction models to simulate biological phenomena such as protein alignment in the membrane at a fast enough rate for real-time experiments. (3) Results: We describe in detail the integration of an implicit membrane model for Integral Membrane Protein And Lipid Association (IMPALA) into our IMS framework. Our implementation can cover multiple levels of representation, and the degrees of freedom can be tuned to optimize the experience. We explain the validation of this model in an interactive and exhaustive search mode. (4) Conclusions: Protein positioning in model membranes can now be performed interactively in real time.

Multisource Fusion UAV Cluster Cooperative Positioning Using Information Geometry

Due to the functional limitations of a single UAV, UAV clusters have become an important part of smart cities, and the relative positioning between UAVs is the core difficulty in UAV cluster applications. Existing UAVs can be equipped with satellite navigation, radio navigation, and other positioning equipment, but in complex environments, such as urban canyons, various navigation sources cannot achieve full positioning information due to occlusion, interference, and other factors, and existing positioning fusion methods cannot meet the requirements of these environments. Therefore, demand exists for the real-time positioning of UAV clusters. Aiming to solve the above problems, this paper proposes multisource fusion UAV cluster cooperative positioning using information geometry (UCP-IG), which converts various types of navigation source information into information geometric probability models and reduces the impact of accidental errors, and proposes the Kullback–Leibler divergence minimization (KLM) fusion method to achieve rapid fusion on geometric manifolds and creatively solve the problem of difficult fusion caused by different positioning information formats and parameters. The method proposed in this paper is compared with the main synergistic methods, such as LS and neural networks, in an ideal scenario, a mutation error scenario, and a random motion scenario. The simulation results show that by using UAV cluster movement, the method proposed in this paper can effectively suppress mutation errors and achieve fast positioning.

Fast Underwater Optical Beacon Finding and High Accuracy Visual Ranging Method Based on Deep Learning.

Visual recognition and localization of underwater optical beacons is an important step in autonomous underwater vehicle (AUV) docking. The main issues that restrict the use of underwater monocular vision range are the attenuation of light in water, the mirror image between the water surface and the light source, and the small size of the optical beacon. In this study, a fast monocular camera localization method for small 4-light beacons is proposed. A YOLO V5 (You Only Look Once) model with coordinated attention (CA) mechanisms is constructed. Compared with the original model and the model with convolutional block attention mechanisms (CBAM), and our model improves the prediction accuracy to 96.1% and the recall to 95.1%. A sub-pixel light source centroid localization method combining super-resolution generative adversarial networks (SRGAN) image enhancement and Zernike moments is proposed. The detection range of small optical beacons is increased from 7 m to 10 m. In the laboratory self-made pool and anechoic pool experiments, the average relative distance error of our method is 1.04 percent, and the average detection speed is 0.088 s (11.36 FPS). This study offers a solution for the long-distance fast and accurate positioning of underwater small optical beacons due to their fast recognition, accurate ranging, and wide detection range characteristics.

Practical Tracking of Permanent Magnet Linear Motor Via Logarithmic Sliding Mode Control

This article focuses on the fast position tracking problem for the permanent magnet linear motor (PMLM) system under a chattering-reduced sliding mode control signal. To this end, a class of globally nonsingular sliding mode control (SMC) laws, called logarithmic sliding mode (LnSM) control, is proposed in this article. Using the natural logarithm function, a high gain is established at the equilibrium of the sliding mode reduced-order system, which leads to a higher tracking precision and a faster local convergence rate than those of some classical SMCs. In addition, a super-twisting algorithm-based LnSM (ST-LnSM) control is constructed to reduce the chattering typical for first-order SMC, while stabilizing the position tracking system rapidly. Since only a few parameters need to be adjusted, and the employed natural logarithm function is conventionally integrated into most PMLM drivers, the proposed control law is easy to implement in PMLM systems or other industrial servo systems.

Fast Positioning Model and Systematic Error Calibration of Chang'E-3 Obstacle Avoidance Lidar for Soft Landing.

Chang’E-3 is China’s first soft landing mission on an extraterrestrial celestial body. The laser Three-Dimensional Imaging (TDI) sensor is one of the key payloads of the Chang’E-3 lander. Its main task is to provide accurate 3D lunar surface information of the target landing area in real time for the selection of safe landing sites. Here, a simplified positioning model was constructed, to meet the accuracy and processing timeline requirements of the TDI sensor of Chang’E-3. By analyzing the influence of TDI intrinsic parameters, a permanent outdoor calibration field based on flat plates was specially designed and constructed, and a robust solution of the geometric calibration adjustment was realized by introducing virtual observation equations for unknowns. The geometric calibration and its absolute and relative positioning accuracy verification were carried out using multi-measurement and multi-angle imaging data. The results show that the error of TDI intrinsic parameters will produce a false obstacle with a maximum height of about 1.4 m on the plane, which will cause the obstacle avoidance system of Chang’E-3 to fail to find a suitable landing area or find a false flat area. Furthermore, the intrinsic parameters of the TDI have good stability and the accuracy of the reconstructed three-dimensional surface can reach about 4 cm after error calibration, which provides a reliable terrain guarantee for the autonomous obstacle avoidance of the Chang’E-3 lander.

Development of controller for fast plasma position control coils with ISO-FLUX scheme on JT-60SA

Two types of poloidal magnetic field coils, superconducting poloidal field (SCPF) coils and in-vessel coils called fast plasma position control (FPPC) coils, will be installed in JT-60SA. We presented the different roles of SCPF and FPPC coils. The SCPF coils control plasma position and shape (P/S) and plasma current (I p), whereas the FPPC coils stabilize the perturbation of the n= 0 mode of magnetohydrodynamic (MHD) instability, such as vertical instability. This study developed a controller that outputs a coil voltage command for the power supply connected to each coil based on an ISO-FLUX scheme using an equilibrium control simulation code, MHD equilibrium control simulator (MECS). This controller stabilizes the horizontal and vertical plasma displacements using FPPC coils. FPPC coils have the advantage of FPPC due to fast coil current response; however, the induced current is also driven in FPPC coils. Thus, we proposed a control logic to mitigate the induced currents, particularly when the induced voltage is large. The difference in coil current response for SCPF and FPPC coils causes the coupling problem. Thus, decoupling between the SCPF and FPPC coils was established by employing the derivative treatment on the ISO-FLUX scheme in the FPPC control. To investigate the effectiveness of the FPPC control, using MECS we evaluated the allowable I p disruption intensity, which causes the plasma horizontal displacement, in the high elongation plasma, which relates to the plasma vertical displacement. Higher I p disruption intensity and elongation were allowed by adding the FPPC control. We investigated the controllability in the plasma ramp-up and flat-top operations. The support of FPPC control for SCPF control expands the plasma operation region which contributes to achieving the planned plasma operation in JT-60SA.

Research on Fast and Precise Positioning Strategy of an Ultrasonic Motor Based on the Ultrasonic Friction Reduction Theory.

To address the problems of the large positioning error and long positioning time of the traditional positioning strategy, namely, the two-phase simultaneous power-off method (TPSPM), a new positioning strategy, called the first single-phase then two-phase power-off method (FSPTTPPM), based on the ultrasonic friction reduction theory, has been proposed in this work. This method realizes zero sliding displacement between the friction material and the stator during the torsional oscillation of the shaft by controlling the driving circle frequency and the duration of the single-phase power-off period, which reduces the deviation of the displacement reservation value. In order to verify the correctness of the driving mechanism, a test platform has been built, and two positioning strategies have been used for experimental verification. The following experimental results have been obtained: compared to TPSPM, FSPTTPPM has the advantages of higher positioning accuracy and short positioning time. In terms of the positioning accuracy, the relative errors of the displacement reservation values of FSPTTPPM and TPSPM vary with the initial angular velocity (0.24 to 1.18 rad/s) in the range of −0.4 to 0.1 and −0.8 to 0.8, respectively. In addition, the relative error of the displacement reservation value is closer to zero than that of TPSPM at the same initial angular velocity. In terms of the positioning time, when the initial angular velocity is greater than 0.7 rad/s, the positioning time of the FSPTTPPM is approximately 10 ms smaller than that of the TPSPM.

Multi-line laser structured light fast visual positioning system with assist of TOF and CAD

As a reliable and high-precision three-dimensional (3D) vision method, line laser structured light vision has been widely used in the engineering field. However, to obtain overall 3D shape of target to be measured, scanning mechanisms need to be added. Multi-line laser structured light vision can obtain multi-line array 3D shape of workpiece without scanning; however, the encoding of multi-line lasers is a difficult task. This paper proposes a composite vision system, which is composed of time-of-flight(TOF) camera, color camera and vertical cross multi-line laser structured light. Color camera and multi-line laser form a multi-line array 3D vision system, while the coded signal of multi-line laser stripes is provided by TOF camera and corresponding coding algorithm is also proposed in this paper. Based on this system, automatic positioning of welding seam is realized by registration of CAD data and multi-line laser 3D data. The registration is divided into two steps, which are coarse registration and precise registration. Coarse registration is performed by using CAD point cloud data and original point cloud data of multi-line laser; while precise registration is performed with CAD welding seam point cloud data and welding seam point cloud data of multi-line laser. This paper also analyzes accuracy of vision system based on constructing structured light vision model. The measurement accuracy of vision system in x, y and z directions is 0.25, 0.06 and 0.29 mm respectively. This composite vision system can realize precise positioning of target within a single exposure time, which provides possibility for positioning under movement.