Kinematic Level Research Articles

Inoculation of maize seeds with Pseudomonas putida leads to enhanced seedling growth in combination with modified regulation of miRNAs and antioxidant enzymes

Bacteria that positively interact with plant roots are defined as plant growth promoting rhizobacteria (PGPR). Although the positive effect of PGPR on plant growth has been widely studied, their impact on genetic regulation during plant growth processes remains largely unknown. Therefore, this study aimed to gain a deeper understanding of the regulatory role of miRNA and redox enzymes in response to PGPR at the maize seedling stage in leaf growth zone which consists of the meristem, elongation and mature zones. For this purpose, growth of the third leaf was monitored in response to Pseudomonas putida (P. putida) KT2440 at phenotypic, physiological, cellular, kinematic, and transcriptional levels. This application resulted in an increase of 15% in shoot length, 56% in both shoot fresh/dry weight, 10% in chlorophyll amount, 8% in mature cell length, 15% in leaf elongation rate, and 7% in cell production; meanwhile final leaf length was unchanged, while leaf area and leaf width decreased by 22% and 16%, respectively. Ascorbate peroxidase and glutathione reductase activity increased throughout the leaf growth zone indicating a possible role in PGPR-plant interaction during transition between cell division, expansion and differentiation processes. The expression analysis of cell cycle check point marker genes revealed that CycA2_1 was mainly responsible for promoting cell proliferation in meristem. miR160, miR169 and miR408 were differentially expressed in the meristem, indicating their indirect regulatory roles in the cell division response to PGPR. In addition, miR160, miR319 and miR396 were downregulated in the elongation zone, which draws attention to their possible role in regulating cell elongation processes. In summary, cell cycle, redox and miRNA regulation in maize seedling growth zones in response to P. putida were investigated for the first time in this study.

Path-Guided Containment Maneuvering of Mobile Robots: Theory and Experiments

This article investigates the path-guided containment maneuvering of networked two-wheeled mobile robots with multiple virtual leaders moving along multiple parameterized paths. A two-level cooperative control architecture is proposed to achieve a containment formation. At the kinematic level, distributed guidance laws and path update laws are developed for mobile robots and virtual leaders, respectively. Containment maneuvering errors are involved in the path update laws design to enforce the coordination between mobile robots and virtual leaders. At the kinetic level, two extended state observers are utilized to estimate the unknown uncertainties existing in surge and yaw dynamics. Then, antidisturbance kinetic control laws are developed through the estimated uncertainties. By using the proposed controllers, the states of mobile robots not only converge to the convex hull spanned by multiple virtual leaders, but also keep a certain formation pattern specified by the convex combination of virtual leaders. The input-to-state stability of the closed-loop path-guided containment maneuvering system is analyzed through Lyapunov theory. The effectiveness of the presented method is verified via experiment on CSICET-MR01 mobile robots.

Quantitative Assessment of Upper-Limb Motor Function for Post-Stroke Rehabilitation Based on Motor Synergy Analysis and Multi-Modality Fusion.

Functional assessment is an essential part of rehabilitation protocols after stroke. Conventionally, the assessment process relies heavily on clinical experience and lacks quantitative analysis. In order to objectively quantify the upper-limb motor impairments in patients with post-stroke hemiparesis, this study proposes a novel assessment approach based on motor synergy quantification and multi-modality fusion. Fifteen post-stroke hemiparetic patients and fifteen age-matched healthy persons participated in this study. During different goal-directed tasks, kinematic data and surface electromyography(sEMG) signals were synchronously collected from these participants, and then motor features extracted from each modal data could be fed into the respective local classifiers. In addition, kinematic synergies and muscle synergies were quantified by principal component analysis (PCA) and k weighted angular similarity ( k WAS) algorithm to provide in-depth analysis of the coactivated features responsible for observable movement impairments. By integrating the outputs of local classifiers and the quantification results of motor synergies, ensemble classifiers can be created to generate quantitative assessment for different modalities separately. In order to further exploit the complementarity between the evaluation results at kinematic and muscular levels, a multi-modal fusion scheme was developed to comprehensively analyze the upper-limb motor function and generate a probability-based function score. Under the proposed assessment framework, three types of machine learning methods were employed to search the optimal performance of each classifier. Experimental results demonstrated that the classification accuracy was respectively improved by 4.86% and 2.78% when the analysis of kinematic and muscle synergies was embedded in the assessment system, and could be further enhanced to 96.06% by fusing the characteristics derived from different modalities. Furthermore, the assessment result of multi-modality fusion framework exhibited a significant correlation with the score of standard clinical tests ( R = - 0.87, P = 1.98e - 5 ). These promising results show the feasibility of applying the proposed method to clinical assessments for post-stroke hemiparetic patients.

On age-dependent bone remodeling

A number of previous studies have investigated the possibilities of modelling the change in density of bones. Remodeling can be formulated at the constitutive or the kinematic level. In this work we introduce a formulation for the density growth process which takes not only the mechanical stimulus into account but also the influence of age on the evolution of growth. We demonstrate the implementation in the context of the finite element method. This novel approach is illustrated for a simple uniaxial extension test and is verified against previous numerical results. Moreover, two further physiologically motivated examples are performed. The results of the proposed modified model show excellent agreement with comparable results from literature and are promising for the application to real-life problems.

Eternally oscillating zero energy universe

The question of whether the universe is eternal or if it had a singular moment of creation is deeply intriguing. Although different versions of steady state and oscillatory models of eternal universe have been envisaged, empirical evidence suggests a singular moment of creation at the big bang. Here we analyze the oscillatory solutions for the universe in a modified theory of gravity THED (Torsion Hides Extra-Dimension) and evaluate them by fitting Type 1a supernovae redshift data. THED-gravity exactly mimics General Relativity at the kinematical level, while the modifications in its dynamical equations allow the universe to bounce between a minimum size and a maximum size with a zero average energy within each oscillation. The optimally fit oscillatory solutions correspond to a universe with (i) a small matter density requiring little to no dark matter, (ii) a significantly negative spatial curvature, (iii) a tiny negative dark energy. Alternatively, there exists non-oscillating solutions that appear as an ever-expanding universe from a single bounce preceded by a collapse from the infinite past. These ever-expanding solutions provide marginally better fits to the supernova redshift data, but require larger matter densities and positive dark energy along with a positive spatial curvature. A qualitative analysis of CMB power spectrum in the modified theory suggests a significant negative spatial curvature, which is in stark contrast to a near-zero curvature in the standard big bang theory. An independent constraint on the spatial curvature can further shed light on discriminating the ever expanding and oscillatory universe scenarios.

Targeting Posture Control With Dynamic Obstacle Avoidance of Constrained Uncertain Wheeled Mobile Robots Including Unknown Skidding and Slipping

This article proposes a targeting posture control approach with dynamic obstacle avoidance of differential-drive wheeled mobile robot (WMR) systems in the presence of unknown skidding, slipping, input disturbances, model uncertainties, and torque saturation. First, a nonlinear model predictive control (NMPC) scheme is presented to generate a feasible trajectory from a starting posture to a targeting posture where dynamic obstacles in the environment and physical constraints of the robots are considered. Second, a robust virtual control law at the kinematic level is introduced for the robots to follow the trajectory. Third, taking the consideration of the unknown skidding, slipping, input disturbances, and model uncertainties in the dynamic model being lumped as a total disturbance, which is estimated by the linear extended state observer (LESO), a disturbance compensation-based saturation controller is designed to make the real velocity of the robot converge to the virtual velocity command. Finally, the effectiveness of the proposed control strategy is verified by simulation results.

DO-LPV-based robust 3D path following control of underactuated autonomous underwater vehicle with multiple uncertainties

This study investigates a path following problem of underactuated autonomous underwater vehicle under multiple uncertainties in three-dimensional space. The uncertainties are partly induced by hydrodynamic coefficient uncertainty, ocean currents and unmodeled hydrodynamics, namely dynamic uncertainties. In addition, velocities are assumed to be measured with bounded noise, which is called velocity measurement uncertainties. To address this issue, a compound robust path following control strategy is developed. At the kinematic level, an improved kinematic controller is developed by utilizing disturbance observer to recover the unknown time-varying attack and side-slip angular velocity. At the dynamic level, a novel dynamic tracking model is firstly established via linear parameter varying (LPV) technique, by which multiple uncertainties are expressed in a comprehensive way. Subsequently, a robust LPV controller is employed to track desired velocities generated by kinematic controller, which has less dependence on accurate model and exact velocity measurement. Finally, rigorous stability analysis proves the uniform and ultimate boundedness of path following errors. The comparative numerical results also substantiate the efficacy and superiority of designed method.

Trajectory planning and robust tracking control for a class of active articulated tractor-trailer vehicle with on-axle structure

Traditional articulated vehicles exhibit poor steering performance since there exist no direct rotating moment for the underactuated trailers, which cause such vehicles nearly cannot work well in the narrow space. To overcome this shortcoming associated with the traditional articulated vehicles, an active articulated structure is proposed, in which a steering motor is introduced at the articulated joint of tractor and trailer, in addition to utilizing mecanum wheels as trailer wheels. On the basis of this structure, a coordinated control method is designed to ensure the vehicle kinematics constraints and dynamic maneuverability. The coordination control consists of two level controllers. On the level of kinematics, model predictive control (MPC) is adopted as posture controller, which can solve the non-holonomic problem of the whole active articulated tractor-trailer vehicle system; On the dynamic level, a sliding mode control (SMC) is introduced to design a dynamic controller to track the desired velocities generated online, which can increase the robustness of the system. The simulation results show that the proposed active articulated tractor-trailer vehicle system has better maneuverability compared with the traditional one, and the proposed control strategy can ensure the required control effect.

Adaptive Fuzzy Behavioral Control of Second-Order Autonomous Agents With Prioritized Missions: Theory and Experiments

In this paper, we study the adaptive fuzzy formation control of multiple autonomous agents with prioritized missions. For a platoon of autonomous agents in an unknown environment containing multiple obstacles, formation control is investigated, where each agent is modeled by a second-order nonlinear system under unknown external disturbance in the Brunovsky form. We introduce the systematic procedure of null-space-based projection to convert the prioritized multimission control problem into a behavioral control problem. Then, we further develop a class of nonlinear-fast-terminal-sliding-mode-based adaptive control strategies that combine the fuzzy logic systems by jointly considering both kinematic and dynamic levels of the agents. The proposed controllers can guarantee each individual agent to achieve the predesigned desired pattern and drive the entire systems to achieve the prescribed missions. A simulation example with five agents demonstrates the effectiveness of the algorithm. Finally, the strategies are experimentally validated using a platoon of Pioneer 3AT and 3DX mobile robots.

Flocking and Target Interception Control for Formations of Nonholonomic Kinematic Agents

In this brief, we present solutions to the flocking and target interception problems of multiple nonholonomic unicycle-type robots using the distance-based framework. The control laws are designed at the kinematic level and are based on the rigidity properties of the graph modeling the sensing/communication interactions among the robots. An input transformation is used to facilitate the control design by converting the nonholonomic model into the single-integrator-like equation. We assume only a subset of the robots knows the desired, time-varying flocking velocity, or the target's motion. The resulting control schemes include distributed, variable structure observers to estimate the unknown signals. Our stability analyses prove convergence to the desired formation while tracking the flocking velocity or the target motion. The results are supported by experiments.

Path-guided time-varying formation control with collision avoidance and connectivity preservation of under-actuated autonomous surface vehicles subject to unknown input gains

This paper investigates the distributed time-varying formation control for a swarm of under-actuated autonomous surface vehicles subject to unknown input gains, in addition to model uncertainties and ocean disturbances. The fleet is required to follow a parameterized path with a time-varying formation while avoiding collisions and maintaining connectivity at a complex sea environment. At the kinematic level, a distributed guidance control law is proposed based on a consensus approach, a path-following design, artificial potential functions, and an auxiliary variable approach. At the kinetic level, an adaptive kinetic control law is designed based on an indirect model reference adaptive control approach where a neural estimator is developed for identifying unknown input gains, model uncertainties and ocean disturbances. The stability of the closed-loop system is proven via cascade stability analysis. The advantage of the proposed method is three-folds. First, the developed time-varying formation controller is able to achieve various coordinated behaviors such as cooperative target tracking and target enclosing. Second, the proposed time-varying formation controller is robust against model uncertainties, ocean disturbances and unknown input gains. Third, the proposed distributed controller holds the capability of collision avoidance and connectivity preservation. Simulation results substantiate the effectiveness of the proposed path-guided time-varying formation controllers.

Finite-Time PLOS-Based Integral Sliding-Mode Adaptive Neural Path Following for Unmanned Surface Vessels With Unknown Dynamics and Disturbances

Unmanned surface vessels (USVs) are supposed to be able to adapt unstructured environments by means of multi-sensor active perception without any human interference, and high-accuracy path following is achieved for USVs by effective control strategies and intelligent devices of e-navigation. This paper proposes a finite-time predictor line-of-sight (LOS)-based integral sliding-mode adaptive neural (FPISAN) scheme for the path following of USVs in the presence of unknown dynamics and external disturbances, which copies with the problem of merging with the kinematic level and the kinetic level of USVs. From the point of view of USVs’ practical engineering, the inertia matrix of USVs maintains nonzero off-diagonal. In order to ensure that USVs can converge to and follow a defined path, a novel LOS-based guidance law that can acquire sideslip angles by error predictors within a finite time is presented, called finite-time predictor-based LOS (FPLOS). Then, the path-following control laws are designed by combining the neural network (NN) technique with the integral sliding-mode method, where radial basis function NN (RBFNN) is applied to approximate lumped unknown dynamics induced by nonparametric uncertainties and external disturbances. The theoretical analysis verifies that the path-following guidance-control system of USVs is semiglobally uniformly ultimately bounded (SGUUB) with the aid of Lyapunov stability theory. The effectiveness and performance of this presented scheme are illustrated by simulation experiments with the comparison. Note to Practitioners —The design of heading guidance laws and path-following control laws for path following of USVs subject to unknown dynamics and external disturbances is a critical problem, which affects the development of USVs. This problem associated with practical engineering of USVs due to the actual navigation environment that is complex, diversified, and highly unstructured. This paper presents a wholly tight strategy to compensate for unknown sideslip angles and approximate lumped unknown dynamics. Hence, an effective scheme being denoted FPISAN mentioned above is developed for path following of USVs.

Assessment of Childhood Apraxia of Speech: A Review/Tutorial of Objective Measurement Techniques

Background With respect to the clinical criteria for diagnosing childhood apraxia of speech (commonly defined as a disorder of speech motor planning and/or programming), research has made important progress in recent years. Three segmental and suprasegmental speech characteristics-error inconsistency, lengthened and disrupted coarticulation, and inappropriate prosody-have gained wide acceptance in the literature for purposes of participant selection. However, little research has sought to empirically test the diagnostic validity of these features. One major obstacle to such empirical study is the fact that none of these features is stated in operationalized terms. Purpose This tutorial provides a structured overview of perceptual, acoustic, and articulatory measurement procedures that have been used or could be used to operationalize and assess these 3 core characteristics. Methodological details are reviewed for each procedure, along with a short overview of research results reported in the literature. Conclusion The 3 types of measurement procedures should be seen as complementary. Some characteristics are better suited to be described at the perceptual level (especially phonemic errors and prosody), others at the acoustic level (especially phonetic distortions, coarticulation, and prosody), and still others at the kinematic level (especially coarticulation, stability, and gestural coordination). The type of data collected determines, to a large extent, the interpretation that can be given regarding the underlying deficit. Comprehensive studies are needed that include more than 1 diagnostic feature and more than 1 type of measurement procedure.

A power-based approach to assess the barrelling test's weak solution

Physical simulation of forming is an analytical-experimental branch of mechanical science. Carefully formulated models and their solutions are essential to interpret the simulation data meaningfully and to understand its underlying phenomena. Oversimplified models of deformation and their associated non-unique closed-form solutions are widespread due to the complex and path dependence nature of plastic deformation, its multi-layered governing equations and boundary conditions. Therefore, it is vital to critically evaluate these models at the kinematic level to ensure a reliable outcome.Incremental Profile Modelling (IPM) is proposed as a technique to integrate free surface geometrical data into the solution to address the path dependence issue. IPM also allows quantification of the solution's worthiness without making a reference to the mass or acting forces involved. The technique relies on calculating an equivalent area for a given solution. The area is estimated simply based on the deforming body's geometry and is compared with that of a numerical solution as the reference. The comparison provides a quick and quantitative assessment of the closed-form solution.To demonstrate the technique, the “Barrelling Compression Test” (BCT) is chosen here as a key example. Three kinematic models of the test are considered and their closed-form solutions are obtained and evaluated using IPM. Also, two reference solutions of the test are presented including those of a finite element model and the conventional Cylindrical Profile Model (CPM). The equivalent areas for the first two models and that of the finite element were in good agreement. The third model rendered an “equivalent area singularity” at the sample's centre, and was concluded to be unsuitable to study BCT. The conclusion was not evident purely based on the model's kinematic solution.

High Level Kinematic and Low Level Nonlinear Dynamic Control of Unmanned Ground Vehicles

High Level Kinematic and Low Level Nonlinear Dynamic Control of Unmanned Ground Vehicles

High precision tracking control for a sequence of way-points using dynamic unicycles

This paper investigates the high precision way-point tracking control problems for dynamic unicycles. Firstly, a simplified electrical motor is used to provide the torques in unicycle’s dynamic model. Then, in order to improve the tracking precision, a kinematic controller and a dynamic controller are proposed to drive the unicycle to its given way-points, respectively. A group of parameter conditions is developed for the tracking system to avoid the singularity. Comparing with the other tracking methods, our proposed tracking controllers can effectively drive the dynamic unicycle to its targets with high precision. The stability and performance of proposed tracking method are strictly analyzed in both kinematic and dynamic levels. In final, numerical simulations are provided to verify the effectiveness and advantages of proposed approaches.

Cosmology in mimetic SU(2) gauge theory

It is well known that the standard scalar field mimetic cosmology provides a dark matter-like energy density component. Considering SU(2) gauge symmetry, we study the gauge field extension of the mimetic scenario in spatially flat and curved FLRW spacetimes. Because of the mimetic constraint, the standard Yang-Mills term plays the role of the cosmological constant while the mimetic term provides two different contributions: one is the standard radiation scaling like a−4 while the other contribution in energy density scales as ∝ a−2. Consequently, in the Friedmann equation we have two different energy densities which scale as ∝ a−2: one is the mimetic spatial curvature-like and the other is the standard spatial curvature which can compete with each other. The degeneracy between these two contributions are disentangled in this scenario since the mimetic spatial curvature-like term shows up only at the dynamical level while the standard spatial curvature term shows up at both dynamical and kinematical levels.

On the manipulability of swing foot and stability of human locomotion

Manipulability is a measure that quantifies the range of possible motions of a robotic end-effector and it is also an important measure in the study of coordination of human upper body and grasping tasks. This measure, which is defined on both the kinematic and dynamic level, could be useful in gait, as it could be used to determine potential foot placement possibilities. Kinematic manipulability is defined based on the Jacobian and dynamic manipulability on both the Jacobian and mass-inertia matrix. The main purpose of this study was to evaluate the manipulability of human walking and to explore a possible relation between the manipulability and dynamic stability of walking at different speeds. A 37-DoF tree-like model of the human body was developed to evaluate the manipulability index of human walking. We measured kinematics of 11 healthy male subjects while walking on a treadmill, and mapped the data to the model using inverse kinematics. Jacobian based kinematic/dynamic manipulability measures of walking were evaluated for the swing phase of walking. Manipulability ellipsoids were drawn for geometric determination of this measure in all directions during early, mid- and late swing phases. As stability metrics, the local divergence exponent and Floquet Multipliers were calculated. The results indicated a high kinematic manipulability of the swing foot during early and late swing phases and a drop in kinematic manipulability during mid-swing. Kinematic manipulability of the swing leg during early and late (but not mid-) swing phases increased with walking speed but the average kinematic manipulability of the center of mass and dynamic manipulability of swing foot decreased with increasing walking speed. Moreover, the results showed a weak relation between the manipulability and local and orbital stability.

Output-Feedback Control for Cooperative Diving of Saucer-Type Underwater Gliders Based on a Fuzzy Observer and Event-Triggered Communication

This paper presents an output-feedback control method for cooperative diving of multiple homogenous under-actuated saucer-type autonomous underwater gliders (AUGs) subjected to unmeasured velocities, model uncertainties, as well as unknown environmental disturbances. A robust cooperative diving controller is constructed by using a modular back-stepping design method. First, a fuzzy observer combined with a low-frequency learning scheme is presented to identify the unknown AUG dynamics as well as to estimate the unmeasured velocities. Second, a commanded guidance law is designed based on the observed velocities and a vertical line-of-sight guidance scheme at the kinematic level, and fuzzy dynamic control law is developed at the kinetic level. Finally, a non-periodic path update law based on an event-triggered mechanism is designed to reduce the communication frequency. By using the cascade theory, the stability of the closed-loop system is analyzed. The simulation results are provided to show the effectiveness of the proposed output-feedback control approach for saucer-type AUGs.

Gender effect on underwater undulatory swimming technique of young competitive swimmers

The study aim was determining gender-related differences of underwater undulatory swimming (UUS) kinematic indicators and their impact on UUS velocity. The study included 18 girls (F: age 16.71 ± 0.64 years, FINA points 551 ± 68) and 23 boys (M: age 16.79 ± 0.57 years, FINA points 533 ± 66) training swimming. After marking characteristic anatomical points, subjects performed approximately 7 meters of UUS. A filming device placed behind the underwater window registered the trial. Recordings were analysed using the SkillSpector programme. Boys swam faster (F: 1.24 m/s, M: 1.35 m/s), overcame a greater distance during one cycle (F: 0.67 m, M: 0.74 m), performed movements with higher toes amplitude (F: 0.58 m, M: 0.63 m), obtained higher amplitude and frequency product (F: 1.05, M: 1.15) and smaller ankle joint range of motion (F: 64 °, M: 57 °). In both groups, relationships between velocity and: maximal ankle joint extension, distance covered during one cycle and backward toes shift during downward movement were found. The results were statistically significant ( p < 0.05). Girls and boys differed in kinematic indicator level, but UUS velocity depends on identical kinematic variables, meaning UUS technical training can be performed without gender-division.