High-speed Tracking Research Articles

Effective decarbonization of coal-series kaolin by triboelectric separation based on different motion behaviors of charged particles in electrostatic field

In this work, a rotary triboelectric separation system was set up to study the motion characteristics of charged particles (i.e., kaolinite and coal) using Comsol software simulation and high-speed camera tracking. The results showed that the negatively charged kaolinite particles moved toward the positive electrode, while the positively charged coal particles moved toward the negative electrode. Meanwhile, in horizontal displacement increased with the increase of the charge-to-mass ratio of kaolinite and coal, which favored the decarbonization of coal-series kaolin. Therefore, the effective decarbonization of series-coal kaolin with different particle sizes was achieved via rotary triboelectric separation, in which the decarbonization efficiencies for 0.25–0.50 mm, 0.125–0.25 mm, and 0.074–0.125 mm coal-series kaolin were 41.86%, 45.38%, and 42.66%, respectively. This indicates that the efficient purification and upgrading of coal-series kaolin can be realized via rotary triboelectric separation.

Gas-particle flow of cohesive aluminium powders during laser metal deposition – Experimental and numerical investigation

This paper investigates particle dynamics both inside and outside a Laser Metal Deposition nozzle of a Directed Energy Deposition processing head, i.e. a Laser Metal Deposition (LMD) nozzle, by way of high-speed imaging and particle tracking as well as through computer simulations that account for particle collision and van der Waals forces. It is shown that the particle accumulation phenomena observed experimentally with cohesive aluminium powders can be qualitatively reproduced numerically. It is also demonstrated that such computer simulations can yield the correct order of magnitude for particle velocities, which is rarely reported in the literature and usually unknown for any given LMD system. This work thus paves the way towards more accurate simulations of gas-particle flows in LMD nozzles, especially with cohesive powders.

Size-Dependent Diffusion and Dispersion of Particles in Mucin.

Mucus, composed significantly of glycosylated mucins, is a soft and rheologically complex material that lines respiratory, reproductive, and gastrointestinal tracts in mammals. Mucus may present as a gel, as a highly viscous fluid, or as a viscoelastic fluid. Mucus acts as a barrier to the transport of harmful microbes and inhaled atmospheric pollutants to underlying cellular tissue. Studies on mucin gels have provided critical insights into the chemistry of the gels, their swelling kinetics, and the diffusion and permeability of molecular constituents such as water. The transport and dispersion of micron and sub-micron particles in mucin gels and solutions, however, differs from the motion of small molecules since the much larger tracers may interact with microstructure of the mucin network. Here, using brightfield and fluorescence microscopy, high-speed particle tracking, and passive microrheology, we study the thermally driven stochastic movement of 0.5-5.0 μm tracer particles in 10% mucin solutions at neutral pH, and in 10% mucin mixed with industrially relevant dust; specifically, unmodified limestone rock dust, modified limestone, and crystalline silica. Particle trajectories are used to calculate mean square displacements and the displacement probability distributions; these are then used to assess tracer diffusion and transport. Complex moduli are concomitantly extracted using established microrheology techniques. We find that under the conditions analyzed, the reconstituted mucin behaves as a weak viscoelastic fluid rather than as a viscoelastic gel. For small- to moderately sized tracers with a diameter of lessthan 2 μm, we find that effective diffusion coefficients follow the classical Stokes-Einstein relationship. Tracer diffusivity in dust-laden mucin is surprisingly larger than in bare mucin. Probability distributions of mean squared displacements suggest that heterogeneity, transient trapping, and electrostatic interactions impact dispersion and overall transport, especially for larger tracers. Our results motivate further exploration of physiochemical and rheological mechanisms mediating particle transport in mucin solutions and gels.

Design of a high speed rat whiskers tracking and symmetry analysis system based on FPGA.

This paper presents a high-speed rat whisker tracking and symmetry analysis system based on FPGA. The system utilizes high-speed image sensors recording rat face videos at 120 and 1000 fps. The Xilinx Ultra96 single computer board is chosen as the platform to implement the system's processing system (PS) and the programmable logic (PL) part. The PL part is responsible for high-speed image processing and whisker tracking, while the PS part analyzes the symmetry of rat face using the tracking results from the PL part. With a processing speed FoM of 118.5 fps/GHz on the Xilinx Ultra96 single computer board and 275.47 fps/GHz on a laptop with Intel Core i5-11500T@1.5GHz, the presented system achieves excellent performance. The proposed whisker detection method has a precision of 98.2% when a threshold with a 4-degree error is selected, with an average error angle of 0.98 degrees across more than 10,000 video frames. Moreover, the proposed system is capable of local video processing within millisecond delays. These results demonstrate the feasibility of developing a high-speed, accurate, and efficient whisker tracking and symmetry analysis system for rat behavior research.

Dynamics of nuclear export of pre-ribosomal subunits revealed by high-speed single-molecule microscopy in live cells

We present a study on the nuclear export efficiency and time of pre-ribosomal subunits in live mammalian cells, using high-speed single-molecule tracking and single-molecule fluorescence resonance energy transfer techniques. Our findings reveal that pre-ribosomal particles exhibit significantly higher nuclear export efficiency compared to other large cargos like mRNAs, with around two-thirds of interactions between the pre-60S or pre-40S and the nuclear pore complexes (NPCs) resulting in successful export to the cytoplasm. We also demonstrate that nuclear transport receptor (NTR) chromosomal maintenance 1 (CRM1) plays a crucial role in nuclear export efficiency, with pre-60S and pre-40S particle export efficiency decreasing by 11-17-fold when CRM1 is inhibited. Our results suggest that multiple copies of CRM1 work cooperatively to chaperone pre-ribosomal subunits through the NPC, thus increasing export efficiency and decreasing export time. Significantly, this cooperative NTR mechanism extends beyond pre-ribosomal subunits, as evidenced by the enhanced nucleocytoplasmic transport of proteins.

Sensorless Scheme for Permanent-Magnet Synchronous Motors Susceptible to Time-Varying Load Torques

This paper is devoted to designing a sensorless high-speed tracking control for surface-mount permanent-magnet synchronous motors, considering a time-varying load torque. This proposal consists of an extended-state observer interconnected with a PI-compensated controller, considering only the measurement of electrical variables for feedback. First, to design the extended-state observer, a rotary coordinate model of the motor is extended in one state to estimate the load torque and the rotor’s position and speed. Later, the estimations are fedback to a PI-compensated controller to attenuate the time-varying load torques. Our proposed methodology aims to overcome a restriction regarding the solution of the Riccati equation respecting the Lipschitz condition for observer stability analysis. Therefore, a PI-compensated controller described as a closed-loop provides a sensorless scheme. Lyapunov stability analysis is applied to determine sufficient conditions to ensure that the states of the closed-loop system are ultimately bounded, which is one of our main contributions. The proposed observer-based controller scheme deals with unmeasured load torque fluctuations. Furthermore, we carry out high-precision emulations to provide testing scenarios of the permanent-magnet synchronous motor with some challenging load torque magnitudes and behaviors. Finally, we conduct experiments on the Technosoft® development platform to corroborate the feasibility of the proposed control scheme in a real-world scenario.

Trajectory Guided Robust Visual Object Tracking With Selective Remedy

Siamese trackers have received a lot of attentions due to their promising performance and real-time high speed. However, the robustness is generally limited especially in challenging conditions, such as occlusion. Motivated by that tracking failure does not always occur and the target movement tends to follow certain patterns, in the paper, we propose a generic, fast and flexible approach to improve the robustness of Siamese trackers with two light-load novel modules: Trajectory Guidance Module (TGM) and Selective Refinement Module (SRM). Specifically, TGM encourages to pay a soft attention on possible target location based on short-term historical trajectory. SRM selectively remedies the tracking results at the risk of failure with little impact on the speed. The proposed algorithm can be easily establish upon state-of-the-art Siamese trackers and obtains better performance on seven benchmarks with high real-time tracking speed. The code is available at https://github.com/TJUMMG/TGSR.

Stand-alone Micro Grid based on Artificially Intelligent Neural Network (AI-NN)

INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and a solar photovoltaic system are part of the hybrid energy system, which is effectively employed to meet the energy needs of rural household loads. OBJECTIVE: This research suggests an effective analysis of wind solar hybrid system controllers taking energy demands into account. The controller should be designed in such a way as to intelligently monitor the availability of wind energy and solar energy and store the energy without spilling it out. METHODS: In order to cope with the challenging factors involved in designing the controller, intelligent power tracking with an artificially intelligent neural network (AI-NN) is designed. Added to that, the whole process has been designed and analysed with the MATLAB SIMULINK tool. RESUSTS: The results of the simulation, infer that AI-NN achieved the regression value of 0.99 when compared with the Perturb & Observe algorithm (P&O), and the Fuzzy Logic Control (FLC) algorithm, and has a higher tracking speed. Also, the AI-NN attained 2.62kW whereas the P&O has attained 2.52kW and Fuzzy logic has attained 2.43W of power which is 3.89% higher than P&O algorithm and 7.52% higher than fuzzy MPPT algorithm. CONCLUSION: The designed controller module enhances the system by artificially intelligent algorithm. The AI-NN attains the better power performance with lesser tracking time and higher efficiency. Thus, it is evident that AI-NN MPPT suits well for the hybrid system.

Spatial Adaptive Iterative Learning Control Based High-Speed Train Operation Tracking under External Disturbance

Spatial Adaptive Iterative Learning Control Based High-Speed Train Operation Tracking under External Disturbance

1000× Faster Camera and Machine Vision with Ordinary Devices

In digital cameras, we find a major limitation: the image and video form inherited from a film camera obstructs it from capturing the rapidly changing photonic world. Here, we present vidar, a bit sequence array where each bit represents whether the accumulation of photons has reached a threshold, to record and reconstruct the scene radiance at any moment. By employing only consumer-level CMOS sensors and integrated circuits, we have developed a vidar camera that is 1,000x faster than conventional cameras. By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1,000x faster than human vision. We demonstrate the utility of the vidar camera and the super vision system in an assistant referee and target pointing system. Our study is expected to fundamentally revolutionize the image and video concepts and related industries, including photography, movies, and visual media, and to unseal a new spiking neural network-enabled speed-free machine vision era.

FCR-TrackNet: Towards high-performance 6D pose tracking with multi-level features fusion and joint classification-regression

Tracking an object’s 6D pose is significant in various real-world applications, such as robotic grasping, virtual reality, and self-driving. Still the existing methods suffer from following challenges: i) geometric shapes, such as rotational symmetry shapes, and ii) complex scenes, for instance, cluttered backgrounds and occluded scenes. To tackle these problems, we propose FCR-TrackNet, a novel tracking network that utilizes a residual iterative framework with low-and high-level feature fusion and joint classification-regression. FCR-TrackNet inputs the rendered RGB-D image from the previous frame pose and the current RGB-D image to extract low-level features. Then, high-level features are also obtained by the convolutional network and fused with low-level one to capture subtle variations in target object features across adjacent frames. To reduce computational complexity and ensure high tracking speed, we adopt decoupled branches to estimate the translation and rotation of the pose independently. At last, a joint classification-regression is designed to address the boundary problem of the rotation angle. We introduce a smooth classification label that effectively enhances the accuracy of rotation vector classification. We evaluate the performance of FCR-TrackNet on two well-known datasets, YCB-Video and YCBInEOAT. FCR-TrackNet achieves state-of-the-art ADD values of 94.5% and 93.2%, and ADD-S values of 96.7% and 96.0%, respectively, with a tracking speed of 89.6 Hz. It also outperforms competing algorithms in target pose tracking in occlusion and rotational symmetry shapes. The quantitative and qualitative results validate the high performance of FCR-TrackNet on 6D pose tracking.

Maximum power point tracking techniques using improved incremental conductance and particle swarm optimizer for solar power generation systems

Abstract The generation of power from solar energy by using Photovoltaic (PV) systems to convert the irradiation of the sun into electricity has been adopted over the past years. However, the PV system’s P–V and I–V characteristics become unstable when solar irradiation and temperature change. In this paper, the incremental conductance (INC) has been improved using signals to measure the current and voltage from the PV systems directly which quickly changes with the environmental conditions, and the conventional particle swarm optimization (PSO) is modified so that under multiple shaded peak PV array curves with fast-changing solar irradiance and temperature, more power is extracted at a faster rate without any tracking failure at high-speed tracking of both individual maximum power point (IMPP) and global maximum power point (GMPP) under varying solar irradiance and temperature at a longer distance to enhance the power generated. The individual and global coefficients are also improved to change with multiple shaded peak PV array curves with fast-changing solar irradiance and temperature. DC-DC converter converts DC power from one circuit to another and DC-AC inverter converts DC power to AC power. Simulation was carried out in MATLAB Simulink with different solar irradiance and temperature whereby the conventional INC and PSO were compared with the proposed INC and PSO. An experiment was carried out for a whole day from 8 am to 5 pm to test the validity of the proposed algorithm and compared it with the conventional INC and PSO by using the solar irradiance and temperature received. From both the simulation and experimental results, the proposed INC and PSO performed better by attaining high power and tracking speed with stable output results than the conventional INC and PSO.

Intelligent Tracking Error Prediction and Feedforward Compensation for Nanopositioning Stages With High-Bandwidth Control

In this paper, an intelligent feedforward prediction and compensation scheme to combine with a dual-loop high-bandwidth controller is proposed for high-speed and high-precision tracking control of a nanopositioning stage. Firstly, the dual-loop controller (DLC) consisting of an inner-loop damping and an outer-loop tracking controller is developed with all the parameters optimized simultaneously, which could provide a control bandwidth over the first resonant frequency of the stage. Next, the Gaussian process (GP) machine learning model is employed to capture the dynamic characteristics of the tracking error of the dual-loop controlled plant. Then, a feedforward compensator is constructed to add a compensation term to the initial reference trajectory. Experimental investigations on a self-made piezoelectric-actuated stage validate the effectiveness of the intelligent tracking error prediction method and the excellent performance of the control strategy for high-precision tracking of high-frequency reference trajectories.

Photon-starved snapshot holography

Digital holography (DH) is a powerful imaging modality that is capable of capturing the object wavefront information, making it very valuable for diverse scientific research applications. Generally, it requires ample illumination to enable good fringe visibility and a sufficient signal-to-noise ratio. As such, in situations such as probing live cells with minimal light interaction and high-speed volumetric tracking in flow cytometry, the holograms generated with a limited photon budget suffer from poor pattern visibility. While it is possible to make use of photon-counting detectors to improve the hologram quality, the long recording procedure coupled with the need for mechanical scanning means that real-time extremely low-light holographic imaging remains a formidable challenge. Here, we develop a snapshot DH that can operate at an ultra-low photon level (less than one photon per pixel). This is achieved by leveraging a quanta image sensor to capture a stack of binary holographic frames and then computationally reconstructing the wavefront through integrating the mathematical imaging model and the data-driven processing, an approach that we termed PSHoloNet. The robustness and versatility of our DH system are demonstrated on both synthetic and experimental holograms with two common DH tasks, namely particle volumetric reconstruction and phase imaging. Our results demonstrate that it is possible to expand DH to the photon-starved regime, and our method will enable more advanced holography applications in various scientific imaging systems.

Skywalker: A Compact and Agile Air-Ground Omnidirectional Vehicle

By taking the complementary advantage of multicopters and ground vehicles, air-ground vehicles have shown great potential in various fields due to their superior mobility and outstanding endurance. However, most of the previous works adopt complicated mechanisms, and fail to develop a controller with high precision for tracking challenging trajectories, which severely limits their application. In this work, we firstly propose the design of an air-ground vehicle, which we name as Skywalker, with a concise yet robust mechanism based on an off-the-shelf omnidirectional wheel. Furthermore, we deduce the vehicle's differential flatness considering support and friction forces, and propose a unified controller qualified for high-speed air-ground hybrid trajectory tracking and smooth mode switching. Meanwhile, comprehensive experiments and a benchmark comparison are carried out to validate the system's outstanding performance, where the system tracks trajectories under velocity up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{5.0}~m/s$</tex-math></inline-formula> and saves energy up to 75.2%.

Confocal interferometric scattering microscopy reveals 3D nanoscopic structure and dynamics in live cells

Bright-field light microscopy and related phase-sensitive techniques play an important role in life sciences because they provide facile and label-free insights into biological specimens. However, lack of three-dimensional imaging and low sensitivity to nanoscopic features hamper their application in many high-end quantitative studies. Here, we demonstrate that interferometric scattering (iSCAT) microscopy operated in the confocal mode provides unique label-free solutions for live-cell studies. We reveal the nanometric topography of the nuclear envelope, quantify the dynamics of the endoplasmic reticulum, detect single microtubules, and map nanoscopic diffusion of clathrin-coated pits undergoing endocytosis. Furthermore, we introduce the combination of confocal and wide-field iSCAT modalities for simultaneous imaging of cellular structures and high-speed tracking of nanoscopic entities such as single SARS-CoV-2 virions. We benchmark our findings against simultaneously acquired fluorescence images. Confocal iSCAT can be readily implemented as an additional contrast mechanism in existing laser scanning microscopes. The method is ideally suited for live studies on primary cells that face labeling challenges and for very long measurements beyond photobleaching times.

Full Attitude Control of a Quadrotor Using Fast Nonsingular Terminal Sliding Mode With Angular Velocity Planning

In this article, a fast nonsingular terminal sliding mode combined with angular velocity planning (FNTSM-AVP) controller is developed to achieve high-speed, accurate, and robust attitude tracking performance for a quadrotor. The proposed controller employs a sliding surface function with a continuous arctangent function, which can effectively eliminate chattering behavior on the quadrotor while retaining the speed and accuracy of attitude tracking. Unlike conventional methods, the proposed controller preferentially recovers the roll and pitch angles at desired attitude by planning the shortest arrival path, which is effective to improve the tracking performance. Finally, the finite time convergence and zero tracking error properties of the closed-loop control system under the proposed FNTSM-AVP are analyzed and proved. The aggressive flight experiments demonstrate the advantage of faster convergence and fewer chattering behavior of the proposed method compared to the existing FNTSM controller.

Single Cell Analysis of Inertial Migration by Circulating Tumor Cells and Clusters

Single-cell analysis provides a wealth of information regarding the molecular landscape of the tumor cells responding to extracellular stimulations, which has greatly advanced the research in cancer biology. In this work, we adapt such a concept for the analysis of inertial migration of cells and clusters, which is promising for cancer liquid biopsy, by isolation and detection of circulating tumor cells (CTCs) and CTC clusters. Using high-speed camera tracking live individual tumor cells and cell clusters, the behavior of inertial migration was profiled in unprecedented detail. We found that inertial migration is heterogeneous spatially, depending on the initial cross-sectional location. The lateral migration velocity peaks at about 25% of the channel width away from the sidewalls for both single cells and clusters. More importantly, while the doublets of the cell clusters migrate significantly faster than single cells (~two times faster), cell triplets unexpectedly have similar migration velocities to doublets, which seemingly disagrees with the size-dependent nature of inertial migration. Further analysis indicates that the cluster shape or format (for example, triplets can be in string format or triangle format) plays a significant role in the migration of more complex cell clusters. We found that the migration velocity of a string triplet is statistically comparable to that of a single cell while the triangle triplets can migrate slightly faster than doublets, suggesting that size-based sorting of cells and clusters can be challenging depending on the cluster format. Undoubtedly, these new findings need to be considered in the translation of inertial microfluidic technology for CTC cluster detection.

On the interaction of electroconvection at a membrane interface with the bulk flow in a spacer-filled feed channel

The operational range of electro-driven processes can be extended by (i) reducing diffusion resistances at the membrane/electrolyte interface using spacers and (ii) by electroconvective mixing of the boundary layer at overlimiting current densities. Although many studies have addressed each of these phenomena separately, the details of the interplay of spacer-engineered hydrodynamics and electroconvection are unexplored. In this study, we establish a methodology of a new membrane cell design and the use of a high-speed microparticle tracking velocimetry setup for direct observation and quantification of the 3D velocity field in a spacer-filled electrodialysis channel under process conditions relevant for real electrodialysis applications, i.e., overlimiting currents and elevated Reynolds. We unravel details of the superposition of electroconvective vortices and forced flow velocity with and without an inserted spacer. Overall, the forced flow flattens the vortex structure of electroconvection at increasing Reynolds numbers. In terms of vortex heights, a spacer with intentional dead zones outperforms a commercial spacer that decreases the boundary layer thickness. This study suggests a counter-intuitive spacer design: to exploit electroconvection, an engineered spacer design for maximum use of electroconvection in the far overlimiting region should aim to create intentional regions of low flow velocity.

Complex hemolymph circulation patterns in grasshopper wings

An insect’s living systems—circulation, respiration, and a branching nervous system—extend from the body into the wing. Wing hemolymph circulation is critical for hydrating tissues and supplying nutrients to living systems such as sensory organs across the wing. Despite the critical role of hemolymph circulation in maintaining healthy wing function, wings are often considered “lifeless” cuticle, and flows remain largely unquantified. High-speed fluorescent microscopy and particle tracking of hemolymph in the wings and body of the grasshopper Schistocerca americana revealed dynamic flow in every vein of the fore- and hindwings. The global system forms a circuit, but local flow behavior is complex, exhibiting three distinct types: pulsatile, aperiodic, and “leaky” flow. Thoracic wing hearts pull hemolymph from the wing at slower frequencies than the dorsal vessel; however, the velocity of returning hemolymph (in the hindwing) is faster than in that of the dorsal vessel. To characterize the wing’s internal flow mechanics, we mapped dimensionless flow parameters across the wings, revealing viscous flow regimes. Wings sustain ecologically important insect behaviors such as pollination and migration. Analysis of the wing circulatory system provides a template for future studies investigating the critical hemodynamics necessary to sustaining wing health and insect flight.