Motion State Research Articles

Overview of development and challenges of attitude determination for rotary wing UAVs based on GNSS

Attitude determination of rotary-wing unmanned aerial vehicles (RUAVs) is crucial for grasping their motion state and is a necessary condition to ensure the correct execution of flight missions. With the continuous development and the constant enhancement of measurement accuracy related to the Global Navigation Satellite System (GNSS), attitude determination based on GNSS have become the mainstream high-precision attitude measurement approach. This paper mainly discusses the relevant theories of using GNSS for RUAV’s attitude determination, and introduces the relevent key aspects that determine attitude accuracy in the attitude resolution process, such as integer ambiguity fixing, attitude solution algorithms, and integrated attitude measurement. It especially elaborates on the challenges that faced to be solved for current RUAVs to use the GNSS system for real-time and guarded attitude measurement.

A Robust Navigation Algorithm without GNSS based on Deep Learning and Variational Bayesian Filter

Abstract Integrated navigation systems, combining Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS), are extensively used in land vehicle navigation. However, they often exhibit poor performance during GNSS outages and lack robustness in challenging urban environments. In order to reduce reliance on GNSS and fully leverage the vehicle dynamics hidden in the data, this study proposes a novel robust navigation algorithm without GNSS, based on deep learning and variational Bayesian methods. Firstly, a cascaded Long Short-Term Memory (LSTM) model with an “attitude-velocity” two-step sequential structure is proposed. By incorporating quaternions, it overcomes the non-differentiable property of attitude caused by its bounded nature, resulting in more accurate attitude predictions. Subsequently, the attitude prediction results are utilized to enhance speed prediction, leading to a significant improvement in accuracy. Building upon the cascaded LSTM model, variational Bayesian filtering is employed to further address the complex time-varying error of its results. Through an adaptive data fusion of LSTM predictions and INS data, the data fluctuations are reduced, and the accuracy is significantly improved. The efficacy of the proposed robust navigation algorithm is validated through multiple vehicle experiments conducted on diverse paths. Experimental results demonstrate that even in scenarios where GNSS fails continuously for fifteen minutes, the proposed algorithm maintains of speed and horizontal attitude errors within 0.6m/s (RMSE) and 0.3° (RMSE) respectively. Consequently, the proposed algorithm has broad application prospects in GNSS-denied environments such as building occlusion, underground parking garages, and indoor positioning. In addition, we also provide attempts to improve the model for situations such as odometer assistance and different motion states.

Analysis of noise characteristics of ceramic bearings rotor system in a wide temperature range

Abstract The loosening effect of ceramic bearings in steel seats becomes increasingly pronounced over a wide temperature range as the temperature rises. This leads to more complex bearing movements and more intense contact with the inner walls of the steel seats, significantly impacting the system’s noise characteristics. In the noise model of the ceramic bearing rotor system, the shaft was discretized into elements, and the variable clearance between the bearing and the steel seat due to temperature changes was used as the geometric boundary condition for the outer ring motion. The influence of temperature and clearance on the noise characteristics of ceramic bearings was investigated experimentally. The results indicate that the clearance, by altering the interaction between the bearing and the steel housing, affects the system’s sound radiation. Sound pressure level was positively correlated with temperature increase, and the directionality of the noise also varied with temperature. Following manufacturing requirements, connecting ceramic bearings to the steel housing through an interference fit can effectively mitigate the noise from ceramic bearings. These research findings provide theoretical guidance for the installation and noise suppression of ceramic-bearing rotor systems across a wide temperature range.

Effect of the cervical and thoracic "Daoyin" training on posture and pulmonary function in patients with upper crossed syndrome: a randomized controlled trial.

With the growing ubiquity of electronic devices, the incidence of upper crossed syndrome (UCS) is increasing every year and tends to affect younger populations. The study was designed to assess the effect of cervical and thoracic "Daoyin" training on pain, posture, pulmonary function, cervical range of motion, and emotional state in college students with UCS. We conducted a parallel-group randomized control study. The Fujian Medical University in China. 74 patients with UCS fulfilled the study requirement and were assigned to the intervention group (IG) and the control group (CG). Instructed cervical and thoracic "Daoyin" training was given to students in the IG for eight weeks, five days a week for 45min, whereas students in the CG continued with their usual activities. Primary outcomes, including forward head and shoulder angles, pain and cervical spine function, as well as secondary outcomes, such as pulmonary function, cervical range of motion and emotional state, were measured at baseline and a follow-up of 8-week. These measurements were conducted using photogrammetry, visual analog scale (VAS), Neck Disability Index (NDI), pulmonary function, cervical range of motion test and Self-rating Anxiety Scale (SAS), respectively. The statistical analysis used the change value between the baseline and the 8-week intervention measurements. 74 patients (IG = 37; CG = 37) were randomized. All participants were included in the analysis. There were significant differences of the change values between groups in Forward Head Angle (FHA) (d = 1.113, P < 0.001), Forward Shoulder Angle (FSA) (d = 1.052, P < 0.001), VAS (d = 0.854, P < 0.001), NDI (d = 0.754, P = 0.005), pulmonary function (Forced Expiratory Volume in 1s/Forced Vital Capacity (FEV1/FVC) (d = 0.516, P = 0.002), maximal voluntary ventilation (MVV) (d = 0.504, P = 0.033), cervical range of motion in Left Rotation (LR) (d = 0.647, P = 0.014) and emotional state (d = 0.587, P = 0.014). No side effects were observed in this study. Cervical and thoracic "Daoyin" training can improve the abnormal posture of head forward and round shoulders, reducing pain and anxiety, improving cervical spine function, and improving lung function to a certain extent. ChiCTR2300072669 (20/06/2023), Prospective registration, www.chictr.org.cn .

Exploring the limits of scan time reduction for ferumoxytol-enhanced whole-heart angiography in congenital heart disease patients.

One of the major challenges in CMR is to abbreviate scan times to create shorter protocols that are compatible with clinical workflows. In 3D magnetic resonance angiography (MRA), several strategies have been proposed to shorten scan times, relying on ECG-triggering or self-navigation for motion management. However, these methods are susceptible to heart rate variabilities or respiratory drifts. A similarity-driven multi-dimensional binning algorithm (SIMBA) was introduced to obtain 3D whole-heart angiography from ferumoxytol-enhanced free-running MRI data by extracting distinct motion states. This study explores the limits of acceleration of free-running MRI by leveraging the increase in signal from ferumoxytol by using SIMBA, and its compressed sensing extension XD-MC-SIMBA, while preserving image quality. Data from 6-minute free-running acquisitions of 30 congenital heart disease (CHD) patients were retrospectively undersampled to simulate datasets of 5-, 4-, 3-, 2-, and 1-minute acquisition times. Data-driven SIMBA and XD-MC-SIMBA reconstructions were applied to all datasets. The consistency of the data selection was assessed, and image quality was analyzed by computing different sharpness metrics as a function of undersampling. Image quality was scored using a 5-point Likert scale. Additionally, shorter 3-minute acquisitions were prospectively acquired in nine CHD patients. The motion states selected with SIMBA were consistent across all levels of undersampling, with only 2 out of 30 cases showing completely different data selections. Image quality metrics decreased with increased undersampling, with lower values in SIMBA compared to XD-MC-SIMBA. On average, the diagnostic quality scores were good, with lower scores for 2-minute and 1-minute datasets. Using XD-MC-SIMBA, the quality scores were higher in 43% of cases compared to SIMBA. Moreover 58% of the 1-minute datasets improved to good or excellent quality thanks to XD-MC-SIMBA. All three 3-minute acquisitions were scored as having excellent diagnostic quality. This study demonstrates that ferumoxytol-enhanced free-running MRI can be highly accelerated for 3D angiography in CHD patients when combined with a data-driven SIMBA reconstruction. With the aid of compressed sensing, XD-MC-SIMBA supports the acceleration down to 3minutes or less.

Multiscale modeling of nanofluid flow and enhanced heat transfer via a computational fluid dynamics–discrete element coupled approach

A new multiscale model, which directly considers the interaction between the macroscopic continuous base fluid phase and the microscopic discrete nanoparticle phase, is proposed to analyze the nanofluid flow and enhanced heat transfer. At the macroscale, the flow and heat transfer of nanofluids are modeled by the nonisothermal Navier–Stokes equations under the Eulerian framework. At the microscale, the motion and thermal state of each nanoparticle are governed by a group of ordinary differential equations derived from the Newton's second law and energy balance law under the Lagrangian framework. The models at different scales are coupled together through both interaction force and thermal parameters. To reduce the cost in calculating the interaction force between the two phases, the discrete element method is used. Compared to the existing models, the primary novelties of the present model are twofold. First, the collisions between nanoparticles and between nanoparticles and solid walls are considered to count the heat migration and exchange caused by collisions. Second, the effective thermal conductivity is calculated locally, which establishes the dependence of thermal conductivity on the local spatial distribution of nanoparticles. It is no doubt that these considerations will make the new model more realistic and accurate. To solve the model efficiently, a stable, accurate and decoupled numerical solver is designed by using the finite element method and characteristic-based split scheme. Numerical results show good accuracy of the proposed model and corresponding solver. In particularly, for the nonuniform nanoparticle distribution, the new method has an incomparable advantage over other methods.

UMS-VINS: Unified Monocular-Stereo Features for Visual-Inertial Tightly Coupled Odometry in Degenerated Scenarios

This paper proposes a Unified Monocular-Stereo Visual-Inertial State Estimator (UMS-VINS) that combines monocular, stereo vision, and inertial measurements for vehicle localization in degenerated scenarios. UMS-VINS is a tightly coupled visual-inertial odometry (VIO), which requires a stereo camera and a low-cost inertial measurement unit (IMU). On the one hand, we introduce additional two-dimensional sub-pixel features from the left and/or right cameras. With monocular-stereo features, UMS-VINS can improve the positioning accuracy and robustness by enhancing the quality and quantity of features. On the other hand, a mode selection-based visual-inertial initialization strategy is designed to dynamically choose between stereo visual odometry or VIO according to the inertial motion state and initialization status, which can guarantee successful initialization. The performance on both new real-world and public datasets demonstrates its effectiveness in terms of localization accuracy, localization robustness, and environmental adaptability.

Adaptive Kalman Filter-Integrated navigation measurement using inertial sensor for vehicle motion state recognition

Adaptive Kalman Filter-Integrated navigation measurement using inertial sensor for vehicle motion state recognition

Real-time motion state estimation of feature points based on optical flow field for robust monocular visual-inertial odometry in dynamic scenes

Real-time motion state estimation of feature points based on optical flow field for robust monocular visual-inertial odometry in dynamic scenes

Reinforcement learning-based trajectory tracking optimal control of unmanned surface vehicles in narrow water areas.

For unmanned surface vehicles (USVs) navigating in narrow water areas in the presence of unknown dynamics and ocean environmental disturbances, this paper develops a reinforcement learning (RL)-based optimal control scheme for the trajectory tracking of USVs under motion state constraints. A nonlinear map is introduced to transform constrained motion state errors into bounded transformed errors, and then the motion state-constrained trajectory tracking problem of USVs is equivalently transformed into a boundedness problem of the transformed errors. Furthermore, an actor-critic framework is developed by utilizing adaptive neural networks (NNs). Within the actor-critic framework, a novel weight update law is designed for the critic NN by combining the gradient descent approach and the concurrent learning technology, thereby relaxing the persistent excitation condition required for adaptive critic NN weight updates. Subsequently, a disturbance compensator is designed and combined with the actor-critic framework to learn the trajectory tracking optimal control law for USVs in the presence of unknown dynamics and disturbances. Finally, theoretical analyses prove that the developed control scheme guarantees the boundedness of all signals in the USV closed-loop trajectory tracking control system, and simulation results show that the developed control scheme can make USVs track the desired trajectory in narrow water areas while reducing the energy consumption by approximately 14.6 % compared with an existing controller.

Fault-tolerant reconfiguration estimation and control of vehicle state under sensor fault

Purpose The purpose of this study proposes a strategy based on vehicle kinematics, dynamics and fusion estimation. The estimation signal of vehicle driving state is crucial for vehicle driving safety and stability control, and the issue of fault-tolerant reconstruction estimation of vehicle driving state under the failure of yaw rate or lateral acceleration sensors is a significant research topic. Design/methodology/approach A strategy based on vehicle kinematics, dynamics and fusion estimation is proposed. To address the issue of inaccurate calculation of tire forces because of sensor failure, a method combining adaptive sliding mode observer, genetic algorithm and particle swarm optimization algorithm is proposed to accurately calculate tire forces, and the Square Root Cubature Kalman Filter algorithm is used to reconstruct the estimation of vehicle driving state under sensor failure. To improve the accuracy of fault-tolerant reconstruction estimation of vehicle driving state, an error-weighted multi-method fusion estimation strategy for vehicle driving state is proposed. A fast terminal sliding mode control algorithm is proposed to control the stability of the fault-tolerant reconstruction estimation signal of vehicle driving state. Findings Simulation results show that the proposed fault-tolerant reconstruction estimation algorithm for vehicle driving state can accurately estimate the actual driving state of the vehicle and stably participate in the vehicle stability control system, achieving fault-tolerant reconstruction estimation and control of vehicle driving state under sensor failure. Originality/value The problem of vehicle motion state estimation under yaw velocity sensor fault or lateral acceleration sensor fault is solved, and fault tolerance control under sensor state is realized.

Safe self-adjusting trajectory tracking control method for air cushion vehicle

ABSTRACT The safety of autonomous driving systems is a critical factor in the operation of high-speed air cushion vehicle (ACV). This paper presents a safety-guaranteed trajectory tracking controller for ACV. A safe self-adjusting speed guidance law is developed based on the finite-time auxiliary system. It can autonomously regulate tracking errors in accordance with the vehicle’s motion states and control inputs. Building on this framework, a trajectory tracking controller is developed utilising Lyapunov stability theory and finite-time control techniques to ensure safe operation. The stability of the proposed controller is rigorously proven. Simulation results demonstrate that the controller effectively mitigates tracking errors, ensuring that key motion parameters – such as speed, turn rate and drift angle – remain within predefined safety limits. Moreover, the control signals generated by the controller are shown to be compatible with the physical limitations of the vehicle’s actuators during trajectory tracking.

Effects of Human-Like Characteristics in Sampling-Based Motion Planning on the Legibility of Robot Arm Motions

Conveying the intended goal of a robot arm motion has been shown to increase the quality of human-robot collaboration drastically. To this end, optimization-based approaches have been proposed that optimize the legibility of a robot’s motion. However, they are limited in two ways. First, they are typically not validated in environments with obstacles and narrow passages that require collision-free motion planning. Second, they do not consider the influence of the anthropomorphization process that might be caused by a human-like motion or appearance of the arm. This leads to the question of to what extent the legibility of motions is influenced by these factors. In this work, we study the influence of our previously proposed human-likeness function on the legibility of robot arm motions in the context of sampling-based motion planning. We evaluate it against three other motions: a functional motion, a recorded expert motion, and a legible motion based on a heuristic for the observer’s prediction. For this, we conduct an extensive user study with 94 participants. In contrast to other works, we manipulate the robot’s appearance and the complexity of the environment. We thus provide insights into how the legibility of robot motions is influenced by human-like characteristics in motion, appearance and restricting workspace conditions. The complete stimulus material used in this work is provided at https://mytuc.org/zpvt .

Comparison of flexible strain sensors based on liquid metals with different microchannel structures

Abstract Flexible strain sensors based on fluid microchannels have been widely used in flexible electronics due to their excellent performance. However, the current research ignores the effect of different microchannel structures on the performance of flexible sensors, which is unsuitable for a specific practical application. Therefore, in this paper, sensors with microchannel of straight, wavy, and triangular structures were developed, and the performances of these sensors were compared from the results of simulation and experiment, respectively. The results show that the flexible strain sensors based on these three microchannels have extremely low hysteresis performance. Compared to the strain-stress hysteresis of the straight and wavy sensors, triangular sensors have the lowest hysteresis about 1.713%. Consistently, the triangular sensors also have the lowest hysteresis about 0.229% under strain–resistance response among these sensors. However, the straight sensors have the highest sensitivity among them. In different angles of the same microchannel group, the 180-degree wavy and 90-degree triangular sensors have the lowest hysteresis. Finally, the 90-degree triangular sensor was successfully used to detect the motion states of the human body and robotic finger. The research in this paper provides new ideas for choosing which microchannel of flexible strain sensors to be used in the field of wearable electronics.

A Novel Real-Time Autonomous Localization Algorithm Based on Weighted Loosely Coupled Visual–Inertial Data of the Velocity Layer

IMUs (inertial measurement units) and cameras are widely utilized and combined to autonomously measure the motion states of mobile robots. This paper presents a loosely coupled algorithm for autonomous localization, the ICEKF (IMU-aided camera extended Kalman filter), for the weighted data fusion of the IMU and visual measurement. The algorithm fuses motion information on the velocity layer, thereby mitigating the excessive accumulation of IMU errors caused by direct subtraction on the positional layer after quadratic integration. Furthermore, by incorporating a weighting mechanism, the algorithm allows for a flexible adjustment of the emphasis placed on IMU data versus visual information, which augments the robustness and adaptability of autonomous motion estimation for robots. The simulation and dataset experiments demonstrate that the ICEKF can provide reliable estimates for robot motion trajectories.

Quantifying spatial and dynamic lung abnormalities with 3D PREFUL FLORET UTE imaging: A feasibility study.

Pulmonary MRI faces challenges due to low proton density, rapid transverse magnetization decay, and cardiac and respiratory motion. The fermat-looped orthogonally encoded trajectories (FLORET) sequence addresses these issues with high sampling efficiency, strong signal, and motion robustness, but has not yet been applied to phase-resolved functional lung (PREFUL) MRI-a contrast-free method for assessing pulmonary ventilation during free breathing. This study aims to develop a reconstruction pipeline for FLORET UTE, enhancing spatial resolution for three-dimensional (3D) PREFUL ventilation analysis. The FLORET sequence was used to continuously acquire data over 7 ± 2 min in 36 participants, including healthy subjects (N = 7) and patients with various pulmonary conditions (N = 29). Data were reconstructed into respiratory images using motion-compensated low-rank reconstruction, and a 3D PREFUL algorithm was adapted to quantify static and dynamic ventilation surrogates. Image sharpness and signal-to-noise ratio were evaluated across different motion states. PREFUL ventilation metrics were compared with static 129Xe ventilation MRI. Optimal image sharpness and accurate ventilation dynamics were achieved using 24 respiratory bins, leading to their use in the study. A strong correlation was found between 3D PREFUL FLORET UTE ventilation defect percentages (VDPs) and 129Xe VDPs (r ≥ 0.61, p < 0.0001), although PREFUL FLORET static VDPs were significantly higher (mean bias = -10.1%, p < 0.0001). In diseased patients, dynamic ventilation parameters showed greater heterogeneity and better alignment with 129Xe VDPs. The proposed reconstruction pipeline for FLORET UTE MRI offers improved spatial resolution and strong correlation with 129Xe MRI, enabling dynamic ventilation quantification that may reveal airflow abnormalities in lung disease.

Computer Vision and Advanced Computational Algorithms for Risk Assessment and Performance Enhancement in Track and Field Teaching

This paper discusses the application of computer vision and advanced calculation algorithm in evaluating the teaching risk and teaching effect of track and field. Because of the inherent uncertainty and risk of PE and sports activities (especially track and field), it is necessary to establish an effective risk management mechanism. Using computer vision technology, this paper puts forward a method of analyzing and processing video data to detect and track moving objects, so as to identify potential risks in real time. This method not only improves the safety of students in track and field classes, but also provides valuable insights for improving teaching methods and reducing sports injuries. This paper discusses the background subtraction motion detection algorithm, which is very important for dynamic image modeling and shadow suppression, and can realize accurate motion state detection. The ultimate goal is to ensure the healthy development of school sports and optimize the teaching results of track and field sports.

How do red foxes (Vulpes vulpes) explore their environment? Characteristics of movement patterns in time and space

BackgroundMany animals must adapt their movements to different conditions encountered during different life phases, such as when exploring extraterritorial areas for dispersal, foraging or breeding. To better understand how animals move in different movement phases, we asked whether movement patterns differ between one way directed movements, such as during the transient phase of dispersal or two way exploratory-like movements such as during extraterritorial excursions or stationary movements.MethodsWe GPS collared red foxes in a rural area in southern Germany between 2020 and 2023. Using a random forest model, we analyzed different movement parameters, habitat features—for example landclasses and distances to linear structures—and time variables (season and time of day) within red fox exploratory, transient and stationary movement phases to characterize phase specific movement patterns and to investigate the influence of different variables on classifying the movement phases.ResultsAccording to the classification model, the movement patterns in the different phases were characterized most strongly by the variables persistence velocity, season, step length and distance to linear structures. In extraterritorial areas, red foxes either moved straight with high persistence velocity, close to anthropogenic linear structures during transient movements, or more tortuously containing a higher variance in turning angles and a decrease in persistence velocity during exploratory-like movements. Transient movements mainly took place during autumn, whereas exploratory-like movements were mainly conducted during winter and spring.ConclusionMovement patterns of red foxes differ between transient, exploratory and stationary phases, reflecting displacement, searching and resident movement strategies. Our results signify the importance of the combined effect of using movement, habitat and time variables together in analyzing movement phases. High movement variability may allow red foxes to navigate in extraterritorial areas efficiently and to adapt to different environmental and behavioral conditions.

A laser tracking attitude dynamic measurement method based on real-time calibration and AEKF with a multi-factor influence analysis model

Abstract To address the limitations of six-degree-of-freedom (6-DOF) visual tracking systems in terms of low dynamic performance and the inability to perform measurements under light occlusion, this paper proposes a novel laser tracking attitude dynamic measurement method integrating vision and inertial measurement unit (IMU). A tailored real-time calibration model is developed to enable precise alignment of the vision and IMU coordinate systems during dynamic operations. To overcome the limitations of extended Kalman filter (EKF) that rely on static noise assumptions in complex dynamic measurement scenarios, this study proposes an adaptive mechanism based on multi-factor influence analysis. Through dynamic monitoring of visual observation noise, an adaptive EKF algorithm is designed to enhance performance under varying conditions. When integrated into a vision/IMU fusion system, the algorithm significantly enhances the system’s sensitivity to variations in visual sensor observation noise caused by changes in lighting and motion states. This capability allows rapid adjustment of filtering parameters, leading to substantial improvements in filtering accuracy and stability. Simulation results demonstrate that the proposed algorithm outperforms traditional EKF in fusion measurement accuracy when tested in simulated noise environments featuring sinusoidal and random jump signals. Furthermore, the fusion measurement accuracy is mainly influenced by the data density of the visual sensor and the measurement distance. Finally, the proposed method was validated on a precision turntable. Experimental results reveal that at a 3 m measurement distance and within a 0°–25° angular range, when the turntable rotates at a constant speed of 5°/s along a single axis, the maximum absolute deviation in repeatability of the fused attitude measurements was below 0.11°, and the system is capable of achieving a high measurement frequency of 100 Hz.

Effect of a novel motion and simultaneous irrigation on the cyclic fatigue resistance of Hyflex EDM OneFile.

The aim of this study was to assess the cyclic fatigue resistance of a single-file system (i.e., Hyflex EDM OneFile), during continuous rotation and reflex dynamic motion with and without irrigation. Cyclic fatigue tests were conducted on 48 new Hyflex EDM One files using two different motions, with and without irrigation. The files were randomly assigned to four groups (n = 12) based on the tested motion and irrigation conditions: continuous rotation and the novel kinematics ReFlex Dynamic motion, with and without irrigation. The dynamic fatigue resistance was measured as the number of cycles to fracture (NCF) in an artificial zirconium canal with a 60° angle and a 5mm radius of curvature at an intracanal temperature. The results were analyzed using the non-parametric Mann-Whitney test, with a significance level established at 5% (p < 0.05). The fractured instruments were examined with a scanning electron microscope. The instruments activated in continuous rotation, irrespective of irrigation conditions, demonstrated significantly higher NCF compared to those in ReFlex Dynamic (p < 0.05). Irrigation significantly impacted the cyclic fatigue resistance of Hyflex EDM in ReFlex Dynamic motion (p < 0.05), while it did not influence the resistance of files tested under continuous rotation (p > 0.05). Within the limitations of this in vitro study, HyFlex EDM One files tested under continuous rotation showed greater resistance to cyclic fatigue compared to those tested with ReFlex Dynamic motion, regardless of irrigation. Continuous hypochlorite irrigation enhanced the cyclic fatigue resistance only of the files tested in ReFlex Dynamic motion.