Trajectory Method Research Articles

Foraging trail traffic rules: a new study method of trajectories of the harvester ants.

Harvester ants are one of the most extensively studied groups of ants, especially the group foraging ants, Messor barbarus (Linnaeus, 1767), which construct long-lasting trunk trails. Limited laboratory investigations have delved into head-on encounters along foraging trails involving workers moving in opposing directions, with fewer corresponding studies conducted in the natural environment. To address this gap, we devised an in-field experimental design to induce lane segregation on the foraging trunk trail of M. barbarus. Using an image-based tracking method, we analyzed the foraging behavior of this species to assess the costs associated with head-on encounters and to figure out the natural coexistence of outgoing and returning workers on a bidirectional route. Our results consistently reveal heightened straightness and speed in unidirectional test lanes, accompanied by an elevated foraging rate compared to bidirectional lanes. This suggests a potential impact of head-on collisions on foraging behavior, especially on foraging efficiency. Additionally, Kinematic analysis revealed distinct movement patterns between outbound and inbound flows, particularly low speed and sinuous trajectories of inbounding unladen workers. The study of encounter rates in two traffic systems hints at the plausible utilization of individual memory by workers within trails, underscoring the pivotal role of encounters in information exchange and load transfer.

Exhaustive State-to-State Cross Sections and Rate Coefficients for Inelastic N2-N2 Collisions using QCT Combined with Neural Network Models.

Using the quasi-classical trajectory method, we systematically studied the state-to-state vibrational relaxation process of N2(v1) + N2(v2) collisions over a wide temperature range (5000-30,000 K). Different temperature dependencies of the single- and multiquantum VV and VT events in various (v1,v2) collisions are captured, with the dominant channel being related to the initial vibrational energy levels (vmax = 50). At a specified relative translational energy, there is a monotonic relationship of the VT cross sections with the vibrational energy level, particularly in high-energy collisions. Additionally, we constructed well-trained neural network models (R-values reaching 0.99) using limited quasi-classical trajectory (QCT) data sets, which can be used to predict the state-to-state cross sections and rate coefficients of the VV processes N2(v1) + N2(v2) → N2(v1 - Δv) + N2(v2 + Δv) and VT processes N2(v1) + N2(v2) → N2(v1 - Δv) + N2(v2) (Δv = ±1, ±2, ±3) for collisions with arbitrary initial vibrational states. This work not only significantly reduces computational resources but also serves as a reference for the study of the state-to-state dynamics of all four-atom collision systems in hypersonic flows.

Adaptive reconstruction of ship trajectory considering motion states

Abstract In response to the presence of noise and missing data in the records of ship trajectories from the Automatic Identification System (AIS), which affects the accuracy of ship traffic flow modeling and knowledge discovery, an adaptive reconstruction method for ship trajectories is proposed, taking into account the state of motion of the ship. This method comprehensively considers latitude, longitude, speed, course, and turn rate in the ship trajectory data and enables the identification and removal of position, speed, and course noise. In addition, the ship’s trajectory is divided into straight segments and turning segments based on the rate of change of the ship’s course. Various interpolation methods are adaptively applied to repair the trajectory. The validation with real ship trajectories shows that the proposed method has higher accuracy than other benchmark methods and provides a solid basis for evaluating ship trajectories.

Bright Tripartite Quantum Steering Generated by Above‐Threshold Optical Parametric Oscillation

AbstractEinstein–Podolsky–Rosen (EPR) steering is the key resources in quantum information processing. EPR steering light sources typically obtained through spontaneous parametric down conversion below a threshold are relatively weak. Strong bright EPR steering light source can be obtained by operating the resonant cavity above the threshold. Here, the quantum steering correlations of the system above the threshold are analyzed using numerical simulations based on the quantum random trajectory method in Wigner representation. By employing the genuine multipartite EPR steering criterion, it is demonstrated that genuine bright tripartite EPR steering can be generated above the threshold, and investigate the influences of the nonlinear parameters on the genuine tripartite EPR steering. The scheme of bright EPR steering light source generated by cascaded nonlinear process can be used as a quantum repeater in quantum communication.

Fast generation of collision-free low-thrust trajectories for asteroid landing using deep neural networks

This study presents a fast generation method of time-optimal low-thrust trajectories based on deep neural networks (DNN) for the collision-free asteroid landings. An equivalent unconstrained differentiable problem is transformed via the introduction of smooth penalty function, so that it can be addressed with the optimal control framework. To efficiently solve the equivalent problem to generate sufficient dataset for training DNNs, a double homotopy method is developed. Specifically, the equivalent problem is connected to the time-optimal control problem without anti-collision through two consecutive simplifications, and a solving process with double backward continuation is also formulated. Besides, two DNN models are constructed to provide high-quality predictions for the minimum glide-slope constraint angle of an initial state, and the initial costates and landing time for time-optimal low-thrust trajectories with anti-collision constraints, respectively. As such, the efficiency of collision-free low-thrust landing trajectory generation is improved significantly. For the cases within the range of training dataset or within a certain extension, the low-thrust landing trajectories with a very small terminal landing error can be generated using the predicted initial costates. Meanwhile, with the high-quality initial costates, the high-precision landing trajectories can be obtained by the double homotopy method in only a few iterative steps. Finally, the promising results in a Bennu collision-free asteroid landing scenario validate the efficiency of the proposed method.

A Self-Adaptive Compression Method for Ship Trajectories without Threshold Setting

Addressing the shortcomings of existing ship trajectory compression methods that rely on the empirical setting of a fixed threshold and face challenges in controlling the spatial similarity before and after compression, this paper proposes a self-adaptive compression method for ship trajectories that does not require threshold setting. Initially, a hierarchical and sequential tree structure based on the trajectory characteristics is constructed to determine the importance of a ship’s trajectory points. Subsequently, the dynamic time warping (DTW) operator is introduced to assess the spatial similarity of the trajectory before and after compression, exploring the laws governing similarity variations in the step changes during the compression process from lower to higher levels of the hierarchical and sequential sequence. Finally, the trajectory point that causes the largest step change in similarity within the hierarchical and sequential sequence is identified, and points at lower levels than this point are discarded, thus achieving the objective of self-adaptive adjustment of the level of compression. Our case study results demonstrate that, compared with existing ship trajectory compression methods based on empirically set thresholds, the proposed method has the following advantages: (1) it does not require presetting a fixed threshold and adaptively determines the degree of compression by identifying the trajectory point that leads to the largest step change in similarity, and (2) under the condition of a similar data compression rate, the DTW calculation value is reduced by approximately 25%, significantly enhancing the similarity of the trajectory before and after compression.

An interval programming method of earth-moon trajectory for manned lunar exploration mission under interval uncertainty

An interval programming method of earth-moon trajectory for manned lunar exploration mission under interval uncertainty

Detecting changes in population trends in infection surveillance using community SARS-CoV-2 prevalence as an exemplar.

Detecting and quantifying changes in growth rates of infectious diseases is vital to informing public health strategy and can inform policymakers' rationale for implementing or continuing interventions aimed at reducing impact. Substantial changes in SARS-CoV-2 prevalence with emergence of variants provides opportunity to investigate different methods to do this. We included PCR results from all participants in the UK's COVID-19 Infection Survey between August 2020-June 2022. Change-points for growth rates were identified using iterative sequential regression (ISR) and second derivatives of generalised additive models (GAMs). Consistency between methods and timeliness of detection were compared. Of 8,799,079 visits, 147,278 (1.7%) were PCR-positive. Change-points associated with emergence of major variants were estimated to occur a median 4 days earlier (IQR 0-8) in GAMs versus ISR. When estimating recent change-points using successive data periods, four change-points (4/96) identified by GAMs were not found when adding later data or by ISR. Change-points were detected 3-5 weeks after they occurred in both methods but could be detected earlier within specific subgroups. Change-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel.

Real-Time Space Trajectory Judgment for Industrial Robots in Welding Tasks

In welding tasks, the repeated positioning precision of robots can generally reach the micron level, but the data of each axis during each operation may vary. There may even be out-of-control situations where the robot does not run according to the set welding trajectory, which may cause the robot and equipment to collide and be damaged. Therefore, a real-time judgment method for the welding robot trajectory is proposed. Firstly, multiple sets of axis data are obtained by running the welding robot, and the phase of the data is aligned by using a proposed algorithm, and then the Kendall correlation coefficient is used to identify and remove weak axis data. Secondly, the mean of multiple sets of axis data with strong correlation is calculated as the standard trajectory, and the trajectory threshold of the robot is set using the μ ± nσ method based on the trajectory deviation judgment sensitivity. Finally, the absolute difference between the real-time axis trajectory and the standard trajectory is used to determine the deviation of the running trajectory. When the deviation reaches the threshold, a forewarning starts. When the deviation exceeds the threshold + σ, the robot is stopped. Take the six-axis welding robot as an example, by collecting the axis data of the robot running multiple times under the same conditions, it is proved that the proposed method can accurately warn the deviation of the running trajectory. The research results have important practical value for the prevention of welding robot accidents in industrial production.

Frailty, Outcomes, Recovery and Care Steps of Critically Ill Patients (FORECAST): a prospective, multi-centre, cohort study

PurposeFrailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI).MethodsThis is a multi-centre prospective cohort study enrolling patients ≥ 50 years old receiving life support > 24 h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6 months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6 months.ResultsIn 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2 years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6 months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6 months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6 months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6 months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients.ConclusionsFrailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention.

Seamless multi‐mode switching controller of four‐switch buck–boost converter based on integrated natural trajectory method

SummaryWith the characteristics of high efficiency and high power density, the four switch buck–boost (FSBB) converter is widely used in electric vehicles, direct current microgrids, and so forth. However, how to achieve smooth switching between different modes of FSBB has always been a hot issue in the theoretical and engineering fields. In this paper, considering the dynamic performance and output voltage or inductance current deviation, a control algorithm with integrated natural trajectory method is designed to realize the switching of different modes of FSBB converter. The proposed control algorithm is based on the theory of large signal natural locus and average natural locus. The normalized phase locus of inductance current and output voltage divides the phase plane into five regions and performs large signal or average switching operations in different regions. Theoretical analysis shows that the proposed control algorithm can achieve the balance between the dynamic performance and output voltage or inductance current deviation of FSBB converter in different mode switching. Finally, the performance of the proposed control algorithm is verified by experiments results.

Quantum dynamics of the P(2D) + H2 (X1[formula omitted]) → PH (X3Σ-) + H(2S) reaction

The title reaction is thought to be important for the astronomical PO formation, which may contribute to the generation of bioavailable H3PO3. Using quasi-classical trajectory (QCT) method, the state-specified (v = 0, j = 0) rate constant of this reaction was calculated. The comparison with previous temperature-averaged QCT rate constant shows that the effect of ro-vibrational excitation is relatively small below 2000 K. Then, the time-dependent wave packet (TDWP) method was applied to investigate the quantum reaction mechanisms, obtaining the state-specified (v = 0, j = 0) reaction probability, integral cross sections and rate constants. The number of partial waves and the integral interval of collision energy considered were rigorously tested to ensure the convergence of the TDWP rate constant below 2000 K. The TDWP rate constant agrees better to the latest experimental results at 291 to 685 K than those from the two QCT calculations. Also, the TDWP calculations can produce relatively reliable rate constants at 700 to 2000 K, where the Arrhenius formula fitted by experimental results ignores the temperature dependence of the activation energy. The calculated rate constants are helpful for modelling the phosphorus chemistry and determining the abundances of the P-bearing species in interstellar media (ISM).

A trajectory planning method for robotic arms based on improved dynamic motion primitives

PurposeTraditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs).Design/methodology/approachThis study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized.FindingsExperiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning.Originality/valueIt provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.

A Study of Multi-Step Sparse Vessel Trajectory Restoration Based on Feature Correlation

A Study of Multi-Step Sparse Vessel Trajectory Restoration Based on Feature Correlation

Pollution Characteristics, Source, and Health Risk Assessment of Metal Elements in PM2.5 Between Winter and Spring in Zhengzhou

A total of 18 metal elements in ambient PM2.5 in Zhengzhou were continuously determined using an online heavy metal observation instrument in January and April, 2021, and the changes in element concentrations were analyzed. Metal elements were traced via enrichment factors, positive matrix factorization (PMF), and a characteristic radar chart. The US EPA health risk assessment model was used to assess the health risks of heavy metals, and the backward trajectory method and the concentration-weighted trajectory (CWT) method were used to evaluate the potential source regions of health risks. The results showed that the element concentrations were higher in spring, and the sum of Fe, Ca, Si, and Al concentrations accounted for 89.8% and 87.5% of the total element concentrations in winter and spring, respectively. Cd was enriched significantly, which was related to human activities. The concentrations of Pb, Se, Zn, Ni, Sb, and K in winter and Cr, Ni, Fe, Mn, V, Ba, Ca, K, Si, and Al in spring increased with the increasing pollution level. The results of PMF and the characteristic radar chart showed that the main sources of metal elements in winter and spring were industry, crust, motor vehicles, and mixed combustion, with industry and mixed combustion pollution occurring more often in winter and crust pollution occurring more often in spring. Significant non-carcinogenic risks existed in both winter and spring with more severe health risks in winter, and Mn caused significant non-carcinogenic risks. The health risks in winter were mainly influenced by Zhengzhou and surrounding cities and long-distance transport in the northwest, and the health risks in spring were mainly influenced by Zhengzhou and surrounding cities.

Coulomb-induced emission time shifts in high-order harmonic generation from H2+

Accurate emission times of high-order harmonic generation (HHG) are vital for high-precision ultrafast detection in attosecond science, but a quantitative analysis of Coulomb effects on this time is absent in the molecular HHG. Here, we investigate the Coulomb-induced emission-time shift in HHG of H2+ with two different internuclear distances R, where the times obtained via the Gabor transform of numerical data from solving the time-dependent Schrödinger equation are used as simulation experiment results. Based on the molecular strong-field approximation, we develop a trajectory-resolved classical model that takes into account the molecular two-center structure. By selecting appropriate electron trajectories and including Coulomb interactions, the classical trajectory method can reproduce Gabor emission times well. This consistence reveals that Coulomb tails cause an emission-time shift of ∼35 as at the R = 2.0 a.u. case and of ∼40-60 as at the R = 2.6 a.u. case under the present laser parameters when compared to the Coulomb-free quantum-orbit model. Our results are of significance to probe the attosecond dynamics via two-center interference.

A MASH simulation of the photoexcited dynamics of cyclobutanone.

In response to a community prediction challenge, we simulate the nonadiabatic dynamics of cyclobutanone using the mapping approach to surface hopping (MASH). We consider the first 500fs of relaxation following photoexcitation to the S2 state and predict the corresponding time-resolved electron-diffraction signal that will be measured by the planned experiment. 397 abinitio trajectories were obtained on the fly with state-averaged complete active space self-consistent field using a (12,11) active space. To obtain an estimate of the potential systematic error, 198 of the trajectories were calculated using an aug-cc-pVDZ basis set and 199 with a 6-31+G* basis set. MASH is a recently proposed independent trajectory method for simulating nonadiabatic dynamics, originally derived for two-state problems. As there are three relevant electronic states in this system, we used a newly developed multi-state generalization of MASH for the simulation: the uncoupled spheres multi-state MASH method (unSMASH). This study, therefore, serves both as an investigation of the photodissociation dynamics of cyclobutanone, and also as a demonstration of the applicability of unSMASH to abinitio simulations. In line with previous experimental studies, we observe that the simulated dynamics is dominated by three sets of dissociation products, C3H6 + CO, C2H4 + C2H2O, and C2H4 + CH2 + CO, and we interpret our predicted electron-diffraction signal in terms of the key features of the associated dissociation pathways.

Study on trajectory optimization of satellite rapid orbit formation flying for space object

This paper proposes a method of collaborative trajectory planning that utilizes convex optimization and IFPSO to tackle the issue of rapid formation reconstruction by multiple satellites in a low Earth circular orbit. The trajectory optimisation in this study uses convex optimisation and takes into account thrust limitations and safety distance. The time optimal solution is replaced by the path optimal solution, resulting in a suboptimal solution. The time-suboptimal trajectory solving method for formation flying using the CVX software is designed. The IFPSO is used to allocate configurations and waypoints for formation reconstruction, with the aim of balancing fuel consumption across the fleet and reducing the overall fuel consumption of the satellite. The effectiveness of the proposed approach is confirmed by numerical simulation. Despite sacrificing some computational efficiency, the method offered can solve the issues of configuration allocation and trajectory optimization.

Research on Intelligent Recognition and Verification System of Football Offside Penalty Based on Artificial Intelligence

An automatic recognition method for ball trajectory and penalty is extensively studied, leveraging computer vision technology. The core hardware components of this system are designed to effectively filter out noise and extract crucial information from the moving track. This enables the system to accurately identify the speed and position of the ball in real-time. To enhance the precision of image segmentation, a novel approach is introduced that utilizes the threshold vector in high-resolution color spaces. This method determines the color of each pixel through bitwise "and" operations between pixel points and subsets. Additionally, a moving window image filtering algorithm is proposed, incorporating trajectory prediction theory. Experimental results demonstrate that this approach significantly reduces recognition errors, resulting in a notably higher accuracy level, making it a promising solution for enhancing the performance of soccer robot systems.

Correction method of servo feed trajectory in block divided EDM for diffusion shaped film cooling holes

Correction method of servo feed trajectory in block divided EDM for diffusion shaped film cooling holes