Track Initiation Research Articles

Adaptive prescribed performance control for nonlinear robotic systems

This paper investigates the problem of asymptotic tracking control of nonlinear robotic systems with prescribed performance. The control strategy is developed based on a modified prescribed performance function (PPF) to guarantee the transient behavior, while the requirements on the accurate initial tracking error in the classical PPF can be remedied. The fuzzy logic system (FLS) is used to approximate the unknown dynamics. In the existing PPF based adaptive control schemes with FLSs, the tracking error does not achieve asymptotic convergence. To address this issue, a robust integral of the sign of the error (RISE) term is incorporated into the control design to reject the FLS approximation errors and external disturbances, such that the asymptotic convergence is achieved. Finally, numerical simulation and experimental results validate the effectiveness of the proposed control scheme.

GETTING SET UP FOR MEANINGFUL MEASUREMENT-BASED CARE: OUTCOMES, INSTRUMENT SELECTION, AND IMPLEMENTATION

Measurement-based care (MBC) involves the administration of psychometric rating scales for initial assessment and outcome tracking during treatment, and the use of the resulting data for clinical decision making. MBC can improve treatment outcome, especially for youth at risk of a poor response. However, uptake remains low. A major barrier is clinician skepticism about the meaningfulness of MBC systems. This Symposium addresses core elements of designing a meaningful MBC approach, including the selection of outcomes and of relevant and valid measurement instruments.

Personality traits of world leaders and differential policy responses to the COVID-19 pandemic

The current study assesses the extent to which government leaders’ personality traits are related to divergent policy responses during the pandemic. To do so, we use data from the Oxford COVID-19 Government Response Tracker initiative (OxCGRT) to measure the speed and magnitude of policy responses across countries and NEGex, a dataset that maps the personality traits of current heads of government (presidents or prime ministers) in 61 countries. We find that world leaders scoring high on “plasticity” (extraversion, openness) were quicker to implement travel restrictions and provide financial relief as well as offered a stronger response in general (average overall response). Whereas, leaders scoring high on “stability” (conscientiousness, agreeableness, emotional stability) offered both quicker and stronger financial relief. Our findings underscore the need to account for the personality of decision-makers when exploring decision-making during the pandemic, and during similar crisis situations.

Position Tracking Constrained Adaptive Output Feedback Control of Robotic Manipulators

Abstract This work presents the design and the corresponding stability analysis of a model-based, joint position tracking error constrained, adaptive output feedback (OFB) controller for robot manipulators. Specifically, provided that the initial joint position tracking error starts within a predefined region, the proposed controller algorithm ensures that the joint tracking error remains inside this region and asymptotically approaches zero, despite the lack of joint velocity measurements and uncertainties associated with the system dynamics. The constraint imposed on the position tracking error term ensures predictable overshoot for the overall system and enables a predetermined transient performance. The need for the joint velocity measurements is removed via the use of a surrogate filter formulation in conjunction with the use of desired model compensation. The stability and the convergence of the closed-loop system are proved via a barrier Lyapunov function (BLF)-based argument. Extensive numerical simulations and experimental studies performed on a two-link, direct-drive robotic manipulator are provided to illustrate the feasibility and effectiveness of the proposed method.

Organizational and Occupational Innovation when Implementing a Covid-19 Live Tracker in VG Newsroom

ABSTRACT Academic research on whether and how innovation during crises results in durable changes in practice remains scant. The Covid-19 pandemic brought with it new opportunities to look at both innovation and transformations in news work during coverage of the breaking news or monster stories related to it. Through semi-structured qualitative interviews at three different times during the pandemic lock down year of 2021, we engaged with a core group (or “heavyweight team”) of editorial managers, digital managers, and an editor-in-chief to generate unique data on this topic. For this inquiry, we enjoyed unique access to the Schibsted-owned VG newsroom in Norway, which was already known for its innovative means of handling disruptive changes and improving practices and routines. Our findings related to VG's Covid-19 Live Tracker initiative in particular suggest that occupational and organizational discourses of professionalism work together to produce altered roles and tasks, empowered interdepartmental teams, and ultimately the trust of both the audience and the authorities.

Assessment of FY-2G, FY-4A, and Himawari-8 Atmospheric Motion Vectors over Southeast Asia and Their Assimilating Impact on the Forecasts of Tropical Cyclone PABUK

The spatial coverage of atmospheric motion vectors (AMVs) over Southeast Asia (SEA) is mainly covered by the Himawari-8 (HIMA-8) and FengYun-2 (FY-2) series satellites in the Global Telecommunication System (GTS). With the launch of FengYun-4A (FY-4A), a new Chinese geostationary satellite, AMVs have enhanced the spatial and temporal resolution data along with allowing for more options of the spectral channels than the FY-2G. This study focuses on the preliminary quality assessments of the FY-2G, FY-4A and HIMA-8 AMVs during a three-month monsoon period, as well as the impact of assimilating AMVs on the numerical weather prediction (NWP) model over SEA. The results show that the qualities of the AMVs from the FY-2G and FY-4A are sensitive to different quality indicator (QI) values, but this is not the case for the HIMA-8. For QI values at 85%, FY-2G and FY-4A AMVs had a monthly mean feature in the monsoon period that were quite comparable to HIMA-8 AMVs, with a few exceptions in this area when three sets of AMVs were validated against NCEP/FNL operational global analysis data; however, the qualities of the AMVs from HIMA-8 were better overall than those from FY-2G and FY-4A. In addition, four experiments were conducted with and without an assimilation of AMVs with a QI at 85% available from FY-2G, FY-4A, and HIMA-8 to assess their impact on tropical cyclone (TC) PABUK from 1 to 4 January 2019. The findings demonstrate that the assimilation of three sets of AMVs diminishes the average initial position error and track forecast error after 42 h when compared to the control experiment. Nevertheless, none of the experiments’ analyses or forecasts of the TC intensity showed a statistically significant development. The findings for FY-2G and FY-4A AMVs may offer a direction forward for the FY AMVs series dataset for future implementation in the global data assimilation system of NWP models, similar to HIMA-8 AMVs, which shows a favourable performance in assimilating AMVs from assorted satellites for SEA forecasts.

Surgical output within the Fast Track Initiative against trachoma in Amhara region, Ethiopia

Trachomatous trichiasis (TT) is the advanced stage of trachoma where lashes touch the globe of the eye causing permanent damage. Without eyelid surgery, TT can lead to irreversible blindness. In 2015 the Ethiopian Ministry of Health launched the Fast Track Initiative with the aim of enhancing the provision of surgical services for TT. The aims of this study were to determine the productivity of individual surgeons during the 2017 Initiative, to compare this productivity with the Ministry's annual target indicator of ≥ 200 surgeries, and to assess the factors associated with surgical output. This retrospective cross-sectional study utilized programmatic data on surgical output from 140 surgeons active from January 2017 through December 2017 in the eastern half of Amhara region, Ethiopia. Data were collected from a surgery monitoring dataset, analyzed, and compared to the performance targets set by the Ministry. The mean annual number of surgeries carried out per surgeon was 169 (standard deviation: 111) for a total of 23,616 surgeries. Among the 140 surgeons, 38% achieved the target set by the Ministry. Location of surgical training site and estimated surgical backlog were signficantly associated with a higher surgery output. An increase in surgical output was observed compared to productivity prior to the Initiative, although the average annual output during the 2017 Fast Track Initiative was lower than the Ministry's target. Using data driven approaches to setting annual productivity goals should be considered, particularly in light of fewer remaining TT cases as a result of the successful Initiative.

Fast wavefront sensing for X-ray optics with an alternating speckle tracking technique.

Advances in accelerator technologies have enabled the continuous development of synchrotron radiation and X-ray free electron laser (XFEL) sources. At the same time, it has been critical to perform in-situ wavefront sensing to aid delivery of high-quality X-ray beams to the end users of these facilities. The speckle-based scanning technique has obtained popularity due to its high spatial resolution and superior sensitivity compared to other wavefront sensing methods. However, these advantages often come at the expense of longer data acquisition times since multiple images have to be collected to derive the necessary wavefront information. Whereas initial speckle tracking techniques could obtain wavefront information relatively quickly, the installation of additional hardware was routinely required to do so. Here, we propose a novel speckle-based approach, termed Alternating Speckle Tracking (AST), to perform fast wavefront sensing within a conventional beamline setup. The wavefront information derived from the new technique has proven to be valuable for many applications that require temporal resolution. Importantly, both horizontal and vertical wavefront information can be simultaneously derived by moving the speckle generator along the diagonal direction. We expect this method will be widely used by the synchrotron radiation and XFEL community in the future.

Design and Experiment of a Prescribed-Time Trajectory Tracking Controller for a 7-DOF Robot Manipulator

Abstract We present an analytical design and experimental verification of trajectory tracking control of a 7-DOF robot manipulator, which achieves convergence of all tracking errors to the origin within a finite terminal time, also referred to as the “settling time.” A key feature of this control strategy is that the settling time is explicitly assigned by the control designer to a value desired, or “prescribed” by the user and that the settling time is independent of the initial conditions and of the reference signal. In order to achieve this beneficial property with the controller, a scaling of the state by a function of time that grows unbounded toward the terminal time is employed. Through Lyapunov analysis, we first demonstrate that the proposed controller achieves regulation of all tracking errors within the prescribed time as well as the uniform boundedness of the joint torques, even in the presence of a matched, nonvanishing disturbance. Then, through both simulation and experiment, we demonstrate that the proposed controller is capable of converging to the desired trajectory within the prescribed time, despite large distance between the initial conditions and the reference trajectory, i.e., in spite of large initial tracking errors, and in spite of a sinusoidal disturbance being applied in each joint.

Adaptive measurement-assignment marginal multi-target Bayes filter with logic-based track initiation

The measurement-assignment marginal multi-target Bayes (AMMTB) filter assigns individual observations to either clutter or an object by maximizing the joint likelihood function of the observation partition. A label is also introduced in this filter to provide the target trajectory. However, the AMMTB filter requires that the initial state and error covariance of a newborn target are known in advance. Therefore it fails to track the target appearing from an unknown location. To address this problem, an optimized AMMTB filter is given and an adaptive establishing method of the newborn trajectory is proposed. By applying the adaptive establishing method of the newborn trajectory to the optimized AMMTB filter, an adaptive AMMTB filter with logic-based track initiation is developed. This filter uses the logic-based track initiation technique to establish the newborn track and employs the least squares technique to form the initial mean vector and error covariance of the newborn track. The assignment-based technique is also used in this filter to associate the observations and targets. Simulation results show that the proposed adaptive AMMTB filter can efficiently detect and track the target with an unknown appearing location. It has a lower computational requirement and less cardinality error, OSPA error and OSPA(2) error than the existing adaptive filters.

Simultaneous Particle Tracking Velocimetry And Pyrometry Of Spatter Particles Ejected During The Laser Power-Bed Fusion Process Using A Spectral Plenoptic Camera

This paper aims to provide a method for simultaneous 3D particle tracking velocimetry and dual-wavelength pyrometry using a single spectral plenoptic camera for uses in spray and flow diagnostics. The spectral plenoptic camera can capture spatial, angular, and spectral information of light from the scene using a single main lens and sensor. Particle tracking is conducted using the Light-Field Ray Bundling algorithm paired with a four-frame best estimate-enhanced track initialization algorithm to generate 3D high-resolution spatial locations and velocity of particles. Secondly, a dual-wavelength pyrometry method was developed to use particle locations from Light-Field Ray Bundling to find the particle spectra for each wavelength, and then calculate temperature using the spectral intensities. This method achieves 3D particle tracking and temperature measurements using a single lens and sensor, which can be applicable for many different flow measurements. The method was applied to the spatter particle generation caused by the Laser Powder-Bed Fusion process, where spatter particles have been found to be detrimental to the manufactured parts. The calculated speeds of the spatter particles are within the expected range, and the tracks show a complex 3D process. The temperature measurements indicate that the detected particles are in the liquid phase, with temperatures greater than 2000ºC. The simultaneous measurements demonstrate an overall deceleration and cooling of particles during their flight. Therefore, this is a viable technique for simultaneous tracking and temperature measurements.

Constrained adaptive fuzzy super-twisting control for space circumnavigation mission with input constraints and rough dynamics information

The 6-DOF attitude-orbit fast synchronous control problem in the space circumnavigation mission is investigated in this paper with dynamics coupling, uncertainties and disturbances, input constraints, and rough dynamical information feedbacks. The orbital-information-based desired angular acceleration information is dynamically compensated via a set of hierarchical fuzzy systems to avoid the derivation operation of orbital states amplifying measurement noise. Since the adaptive laws for updating fuzzy weights are developed based on hyperbolic tangent function, estimation results are updated slowly, even if the initial tracking errors are large. A novel nonsingular practical terminal sliding-mode (PTSM) reduced-order system is proposed for drive tracking errors fast converge with high precision. Benefiting from the absence of information coupling in the derivative of the PTSM function, an observation-based super-twisting algorithm (STA) is employed to establish the PTSM manifold with weakened chattering. Adaptive laws estimate the maximum uncertainty, and an auxiliary system compensates for the input constraints. Simulation results verify the effectiveness of the proposed control scheme.

Improved Siamese Network-Based 3D Motion Tracking Algorithm for Athletes

For the last few years, the application of Siamese network in athletes’ three-dimensional motion tracking has greatly improved the efficiency of sports training. However, the accuracy of the Siamese network tracking algorithm is limited to a large extent. To solve the above problems, based on the channel attention mechanism, the key feature information perception module is innovatively proposed to promote the discriminant ability of the network model and make the network focus on the convolution feature changes of the target. On this basis, an online adaptive mask strategy is proposed, which adapts the subsequent frames according to the output state of the cross-correlation layer learned online to highlight the foreground object. Compared with other algorithms in annotated data set and MOT17 data set, this algorithm has more stable initial tracking performance, significantly improved accuracy compared with the benchmark, and high robustness tracking effect in complex scenes.

Experimental evaluation of Visual‐Inertial Odometry systems for arable farming

AbstractThe farming industry constantly seeks the automation of different processes involved in agricultural production, such as sowing, harvesting and weed control. The use of mobile autonomous robots to perform those tasks is of great interest. Arable lands present hard challenges for Simultaneous Localization and Mapping (SLAM) systems, key for mobile robotics, given the visual difficulty due to the highly repetitive scene and the crop leaves movement caused by the wind. In recent years, several Visual‐Inertial Odometry (VIO) and SLAM systems have been developed. They have proved to be robust and capable of achieving high accuracy in indoor and outdoor urban environments. However, they were not properly assessed in agricultural fields. In this study we assess the most relevant state‐of‐the‐art VIO systems in terms of accuracy and processing time on arable lands to better understand how they behave on these environments. In particular, the evaluation is carried out on a collection of sensor data recorded by our wheeled robot in a soybean field, which was publicly released as the Rosario data set. The evaluation shows that the highly repetitive appearance of the environment, the strong vibration produced by the rough terrain and the movement of the leaves caused by the wind, expose the limitations of the current state‐of‐the‐art VIO and SLAM systems. We analyze the systems failures and highlight the observed drawbacks, including initialization failures, tracking loss and sensitivity to Inertial Measurement Unit saturation. Finally, we conclude that even though certain systems like ORB‐SLAM3 and stereo Multi‐State Constraint Kalman Filter show good results with respect to others, more improvements should be done to make them reliable in agricultural fields for certain applications such as soil tillage of crop rows and pesticide spraying.

Research on the maximum power point tracking method of photovoltaic based on Newton interpolation-assisted particle swarm algorithm

Abstract Solar energy has attracted a lot of attention because it is clean and has no pollution. However, due to the partially shaded condition, the photovoltaic array cannot work uniformly at the maximum power point, resulting in a large power loss. To improve this problem, the research of the maximum power point tracking (MPPT) algorithm is discussed by scholars. In this paper, an improved particle swarm optimization (PSO) algorithm is proposed to achieve the goal of MPPT, which uses Newton interpolation-assisted conventional PSO. After tracking to the maximum power point, the Newton interpolation method is used to calculate the maximum power point, reduce the number of iterations of the conventional PSO algorithm and reduce the steady-state oscillation. The simulation is carried out in MATLAB®/Simulink® and compared with conventional PSO. The results show that the improved PSO has better tracking accuracy and speed than the conventional algorithm, and the initial tracking speed is increased by >30%.

Disturbance Observer-Based Tracking Controller for Uncertain Marine Surface Vessel

In this study, a novel control framework is proposed to improve the tracking performance of uncertain marine vessels which work in enhanced sea states. The proposed control strategy is based on incorporating a fixed-time nonlinear disturbance observer (FTNDO) in a fixed-time convergent backstepping control. More specifically, the FTNDO is developed to reconstruct the total uncertainties due to the system uncertainty and unknown time-varying exterior disturbances. In comparison with the existing disturbance observers, the FTNDO guarantees that the estimation errors will converge to the origin within a predefined time even if the initial estimation errors tend toward infinity. This feature is quite important in the closed-loop system stability analysis as the separation principle does not hold in nonlinear systems. Besides, it does not require the restricting assumption that the upper bound of the lumped uncertainty or its time derivative has to be bounded or known. A backstepping control with a compensation control part is then designed to make the tracking errors converge to the origin within a finite time regardless of initial tracking errors. The compensation control is developed by means of the estimated signal and applied to totally reject the total uncertainty. The global fixed-time stabilization of the closed-loop system is investigated through the Lyapunov stability criterion. Numerical simulation results conducted on an uncertain marine surface vessel confirm the superior control performance and efficiency of the planned method in comparison with the existing disturbance observer-based tracking control strategies.

Automatic data volley: game data acquisition with temporal-spatial filters

Data Volley is one of the most widely used sports analysis software for professional volleyball statistics analysis. To develop the automatic data volley system, the vision-based game data acquisition is a key technology, which includes the 3D multiple objects tracking, event detection and quality evaluation. This paper combines temporal and spatial features of the game information to achieve the game data acquisition. First, the time-vary fission filter is proposed to generate the prior state distribution for tracker initialization. By using the temporal continuity of image features, the variance of team state distribution can be approximated so that the initial state of each player can be filtered out. Second, the team formation mapping with sequential motion feature is proposed to deal with the detection of event type, which represents the players’ distribution from the spatial concept and the temporal relationship. At last, to estimate the quality, the relative spatial filters are proposed by extracting and describing additional features of the subsequent condition in different situations. Experiments are conducted on game videos from the Semifinal and Final Game of 2014 Japan Inter High School Games of Mens Volleyball in Tokyo Metropolitan Gymnasium. The results show 94.1% rounds are successfully initialized, the event type detection result achieves the average accuracy of 98.72%, and the success rate of the events’ quality evaluation achieves 97.27% on average.

Effect of the Azimuth Axis Tilt Error on the Tracking Performance of a Solar Dish Concentrator System

A solar dish concentrator system has a large windward area and heavy structural mass, and under the action of wind loads and self-weight loads, foundation settlement can easily occur and cause the column (the azimuth axis) to tilt. Upon tilting, the azimuth axis is no longer perpendicular to the horizontal plane, causing a tracking error in the service of the solar dish concentrator system. In this paper, a tracking error model of a solar dish concentrator system is established based on the rigid body motion theory, which considers the azimuth axis tilt error. In this model, a radial angle and tangential angle parameters are used to describe the azimuth axis’s tilt angle and tilt direction. Under the tilt error of the azimuth axis, we analyze, in detail, the initial tracking position of a solar dish concentrator system, the system operation area, and the variation rule of tracking performance in long-term operation. The results show that under the azimuth axis tilt error of the solar dish concentrator system, the deviation of the initial tracking position of the solar dish concentrator system in the horizontal or vertical plane will reduce its tracking performance and the stability of tracking performance compared with the initial tracking position being due east. The tracking performance of a solar dish concentrator system and its stability are better in areas with a relatively low latitude. In different areas with close latitude, the tracking performance of the solar dish concentrator system and its stability are better, particularly with lower longitudes. During a whole year operation period, the tracking performance of an solar dish concentrator system in the first quarter and the fourth quarter is relatively better, and its stability in June and July is relatively better. This work can provide a theoretical basis for the installation, debugging, and error control of solar dish concentrator systems.

Efficacy of Cepstral Measures in Voice Disorder Diagnosis: A Literature Review

Introduction: The acoustic analysis is one of the well-known methods for voice evaluation. In recent years, many studies have investigated the cepstral measures compared with the other former acoustic parameters. This review article evaluates the related studies in the cepstral areas to ascertain whether they are efficient in the diagnosis of dysphonia.Materials and Methods: We reviewed the available research studies between 2009 and 2021 narratively in PubMed, Scopus, Google Scholar, and Science Direct databases. The searched keywords included “cepstral peak prominence”, “smoothed cepstral peak prominence”, “instrumental acoustic analysis”, “acoustic”, and “diagnosis”. The articles that investigated the power of Cepstral Peak Prominence (CPP) and its smoothed version (CPPS) to differentiate dysphonia versus normal voice have been included. However, the interventional studies that consider CPP and CPPS as one of their adjunct variables and studies that investigated the relationship of the cepstral measure with other parameters were not included.Results: Recent studies support the efficiency of CPP and CPPS to diagnose dysphonia.Conclusion: It is reasonable for the voice care teams to use CPP and CPPS in the patients’ initial assessment and track the effects of treatment. However, according to the relatively limited number of studies in this area, more studies are required to clarify the efficacy of cepstral measures in different voice pathologies.

Multi-Sonar Distributed Fusion for Target Detection and Tracking in Marine Environment.

The multi-sonar distributed fusion system has been pervasively deployed to jointly detect and track marine targets. In the realistic scenario, the origin of locally transmitted tracks is uncertain due to clutter disturbance and the presence of multi-target. Moreover, attributed to the different sonar internal processing times and diverse communication delays between sonar and the fusion center, tracks unavoidably arrive in the fusion center with temporal out-of-sequence (OOS), both problems pose significant challenges to the fusion system. Under the distributed fusion framework with memory, this paper proposes a novel multiple forward prediction-integrated equivalent measurement fusion (MFP-IEMF) method, it fuses the multi-lag OOST with track origin uncertainty in an optimal manner and is capable to be implemented in both the synchronous and asynchronous multi-sonar tracks fusion system. Furthermore, a random central track initialization technique is also proposed to detect the randomly born marine target in time via quickly initiating and confirming true tracks. The numerical results show that the proposed algorithm achieves the same optimality as the existing OOS reprocessing method, and delivers substantially improved detection and tracking performance in terms of both ANCTT and estimation accuracy compared to the existing OOST discarding fusion method and the ANF-IFPFD method.