Entire Motion Research Articles

Object oriented data analysis of surface motion time series in peatland landscapes

Abstract Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monitoring of vast areas of peatland and prevented targeting areas urgently needing action to halt further degradation. Measured using interferometric synthetic aperture radar (InSAR), peatland surface motion is highly indicative of peatland condition, largely driven by the eco-hydrological change in the peatland causing swelling and shrinking of the peat substrate. The computational intensity of recent methods using InSAR time series to capture the annual functional structure of peatland surface motion becomes increasingly challenging as the sample size increases. Instead, we utilize the behaviour of the entire peatland surface motion time series using object oriented data analysis to assess peatland condition. Bayesian cluster analysis based on the functional structure of the surface motion time series finds areas indicative of soft/wet peatlands, drier/shrubby peatlands, and thin/modified peatlands. The posterior distribution of the assigned peatland types enables the scale of peatland degradation to be assessed, which will guide future cost-effective decisions for peatland restoration.

A Framework for High-Fidelity and Efficient Collapse Fragility Estimation of Structures Using Cluster Analysis

ABSTRACT A clustering-based framework that can select a smaller number of ground motions from the entire ground motion set for collapse fragility estimation of structures while preserving the accuracy is proposed in this study. The bisecting k-means clustering algorithm is applied to the feature space that we construct. The construction is done by using spectral acceleration over a certain period interval to obtain a small number of ground motions until the fragility curve converges. The efficiency and applicability of the proposed framework is successfully demonstrated through a generic set of single-degree-of-freedom systems and six moment-resisting frame buildings having from 1 to 20 stories. The results indicate that collapse fragilities estimated by a smaller number of ground motions selected by using the proposed framework converge to a near optimal value.

Constraining the physical properties of large-scale jets from black hole X-ray binaries and their impact on the local environment with blast-wave dynamical models

ABSTRACT Relativistic discrete ejecta launched by black hole X-ray binaries (BH XRBs) can be observed to propagate up to parsec-scales from the central object. Observing the final deceleration phase of these jets is crucial to estimate their physical parameters and to reconstruct their full trajectory, with implications for the jet powering mechanism, composition, and formation. In this paper, we present the results of the modelling of the motion of the ejecta from three BH XRBs: MAXI J1820$+$070, MAXI J1535–571, and XTE J1752–223, for which high-resolution radio and X-ray observations of jets propagating up to $\sim$15 arcsec ($\sim$0.6 pc at 3 kpc) from the core have been published in the recent years. For each jet, we modelled its entire motion with a dynamical blast-wave model, inferring robust values for the jet Lorentz factor, inclination angle and ejection time. Under several assumptions associated to the ejection duration, the jet opening angle and the available accretion power, we are able to derive stringent constraints on the maximum jet kinetic energy for each source (between $10^{43}$ and $10^{44}$ erg, including also H1743–322), as well as placing interesting upper limits on the density of the ISM through which the jets are propagating (from $n_{\rm ISM} \lesssim 0.4$ cm$^{-3}$ down to $n_{\rm ISM} \lesssim 10^{-4}$ cm$^{-3}$). Overall, our results highlight the potential of applying models derived from gamma-ray bursts to the physics of jets from BH XRBs and support the emerging picture of these sources as preferentially embedded in low-density environments.

Linearizing the vertical scale of an interferometric microscope and its effect on step-height measurement.

The vertical scale calibration of an interferometric microscope is important for establishing traceability of surface topography measurements to the International System of Units (SI) unit of length, the meter. Building on the calibration procedure for the amplification coefficient developed by de Groot and Beverage [Proc. SPIE 9526, 952610 (2015)], this paper describes a calibration procedure that yields the response curve for the entire vertical scan motion of a coherent scanning interferometric microscope. The method requires only a flat mirror as an artifact, a narrow band spectral filter, an aperture to reduce the effective numerical aperture, and the ability to raise and lower the microscope head so that the center of the interferogram can be varied within the scan range. The local frequency of the interferogram is determined by fitting sections of the interferogram to a sinusoidal function. The nonlinearity determined from the local frequency data can be used to estimate the uncertainty in uncorrected vertical height measurements. We describe how optical profile data can be corrected for nonlinearity due to dynamic effects in the scan motion and show that the correction improves the reproducibility of step height measurements by at least a factor of three and close to that of the repeatability.

The synergy complement control approach for seamless limb-driven prostheses

Limb-driven control allows for direct control by using residual limb movements rather than unnatural and complex muscle activation. Existing limb-driven methods simultaneously learn a variety of possible motions, ranging from a residual limb to entire arm motions, from human templates by relying on linear or nonlinear regression techniques. However, the map between a low-dimensional residual limb movement and high-dimensional total limb movement is highly underdetermined. Therefore, this complex, high-dimensional coordination problem cannot be accurately solved by treating it as a data-driven black box problem. Here we address this challenge by introducing the residual limb-driven control framework synergy complement control. Firstly, the residual limb drives a one-dimensional phase variable to simultaneously control the multiple joints of the prosthesis. Secondly, the resulting prosthesis motion naturally complements the movement of the residual limb by its synergy components. Furthermore, our framework adds information on contextual tasks and goals and allows for seamless transitions between these. Experimental validation was conducted using subjects with preserved arms employing an exo-prosthesis setup, and studies involving participants with and without limb differences in a virtual reality setup. The findings affirm that the restoration of lost coordinated synergy capabilities is reliably achieved through the utilization of synergy complement control with the prosthesis.

Vertical Elastic Acceleration Response Spectra for Vrancea Intermediate-Depth Earthquakes

This study is focused on the evaluation of vertical elastic acceleration response spectra for Vrancea intermediate-depth earthquakes in Romania in the context of the ongoing update of the national seismic design code. The ground motion database employed in this research consists of about 500 ground motions recorded during moderate and large Vrancea intermediate-depth earthquakes with moment magnitudes MW ≥ 5.2. The analysis of the dataset showed that a single ground motion recording had a peak ground acceleration larger than 0.20 g. The results of the analyses showed that no significant differences between the control periods of the vertical elastic response spectra as a function of the site class could be inferred. It was also observed that the mean value of the amplification factor computed for the entire ground motion database was about 2.5, irrespective of the earthquake magnitude, site class, or level of horizontal peak ground acceleration. However, larger-magnitude earthquakes generate larger spectral amplifications in the medium- and long-period ranges. The analysis of the ground motions recorded in Bucharest area revealed a magnitude dependency of the control period for the vertical ground motion TC,v. Finally, a single spectral shape for vertical acceleration response spectra characterized by a maximum dynamic amplification factor of 2.5 and control periods TBv and TCv of 0.05 s and 0.60 s is proposed for design purposes. This aspect allows for a major update from the current version of the national seismic design code which proposes control periods of the elastic vertical response spectrum dependent on the horizontal ones. The short-period (at T = 0.2 s) and long-period (at T = 1.0 s) ratios of the vertical acceleration response spectrum to the corresponding horizontal ones are 0.50 and 0.40.

Distributed Fixed-Time Control for Leader-Steered Rigid Shape Formation With Prescribed Performance.

Resorting to the principle of rigid body kinematics, a novel framework for a multirobot network is proposed to form and maintain an invariant rigid geometric shape. Unlike consensus-based formation, this approach can perform both translational and rotational movements of the formation geometry, ensuring that the entire formation motion remains consistent with the leader. To achieve the target formation shape and motion, a distributed control protocol for multiple Euler-Lagrange robotic vehicles subject to nonholonomic constraints is developed. The proposed protocol includes a novel prescribed performance control (PPC) algorithm that addresses the second-order dynamics of the robotic vehicles by employing a combination of nonsingular sliding manifold and adaptive law. Finally, the effectiveness of the proposed formation framework and control protocol is demonstrated through the numerical simulations and practical experiments with a team of four robotic vehicles.

Coordinated Control of Multiple Surface Unmanned Vehicle Clusters under the Influence of Wind Field and Tides

This paper investigates the problem of coordinated control for multiple surface unmanned vehicles in a cluster under the influence of time-varying disturbances such as wind field and tides, based on state feedback controllers. With the rapid development of offshore cluster formation control technology, studying the cluster formation control problem of surface unmanned vehicles in multiple clusters under the influence of wind field and tides in complex and changing sea environments has important practical significance. This paper proposes a complete solution based on the Hamiltonian method. Firstly, each cluster is set to be located within a ellipsoidal virtual container throughout the entire motion process, and the trajectory of the virtual ellipsoid is used as an external state constraint for the cluster. Based on this, the dynamic equation of the system and the corresponding value function under the influence of wind field and tides on the sea surface are established, and the Hamilton–Jacobi–Bellman equation is used to solve the energy constraint and mutual avoidance between clusters and their members to obtain the optimal control and trajectory of each cluster. Finally, numerical simulation results demonstrate the effectiveness of the proposed method.

An Optimal Nonlinear Model Predictive Control- Based Motion Cueing Algorithm Using Cascade Optimization and Human Interaction

Nonlinear model predictive control has been used in motion cueing algorithms recently to consider the nonlinear dynamics model of the system. The entire motion cueing algorithm indexes, including the physical and dynamical constraints of the actuators and physical constraints of passive joints, can be controlled with precision using nonlinear model predictive control. However, several weighting parameters in the nonlinear model predictive control-based motion cueing algorithm (including driving sensation, motion description of the actuators, and passive joints) require proper and laborious tuning to attain an optimal design structure. In this work, the optimal weighting parameters of a nonlinear predictive control-based motion cueing algorithm model are calculated using cascade optimisation and human interaction. A cascade optimisation method consisting of a particle swarm optimisation and genetic algorithm is designed to identify the best weighting parameters compared to those from one optimiser. In addition, the human decision-making units are added to the two-level cascade optimiser to determine the best solution from a Pareto front. The proposed cascade optimiser decreases the run-time with better extraction of the optimal weighting parameters to increase the motion fidelity compared to a single optimiser. It should be noted that the proposed methodology is applied along longitudinal channel. While the same methodology can be applied along lateral, heave and yaw channels for further evaluation of the proposed method. The proposed model is simulated utilising the MATLAB software and the results prove the efficiency of the newly proposed model compared to those from the previous single optimiser in reproducing more accurate motion signals with better usage of the driving motion platform workspace.

Thermo-Pneumatic Artificial Muscle: Air-Based Thermo-Pneumatic Artificial Muscles for Pumpless Pneumatic Actuation.

To make robots more human-like and safer to use around humans, artificial muscles exhibiting compliance have gained significant attention from researchers. However, despite having excellent performance, pneumatic artificial muscles (PAMs) have failed to gain significant traction in commercial mobile applications due to their requirement to be tethered to a pneumatic source. This study presents a thermo-PAM called Thermo-PAM that relies on heating of a volume of air to produce a deformation. This allows for pneumatic actuation using only an electrical power source and thus enables pumpless pneumatic actuation. The actuator uses a high ratio between the heating volume and the deformable volume to produce a high actuation force throughout its entire motion and can produce either contractile or extension motions. The controllability of the actuator was demonstrated as well as its ability to handle heavy payloads. Moreover, it is possible to rely on either positive or negative pressure actuation modes where the positive pressure actuation mode actuates when heated and the negative pressure actuation mode relaxes when heated. The ability to use Thermo-PAMs for different modes of actuation with different operation methods makes the proposed actuator highly versatile and demonstrates its potential for advanced pumpless robotic applications.

Dynamic Behavior of Heavy Water Inside and Outside of Poly (N-Isopropylacrylamide) (PNIPAM) Microgel Using Broadband Dielectric Spectroscopy

One pot free radical precipitation polymerization was used to synthesize an aqueous suspension of non-ionic poly ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -isopropylacrylamide) [PNIPAM] microgel particles. For dielectric measurements in the frequency range of 100 MHz to 50 GHz and temperature range of 288 K to 323 K, 10 wt. % of freeze-dried PNIPAM microgels dispersed in heavy water were used. The relaxation process was seen at around 15 GHz, which corresponds to the entire rotational motion of the heavy water, both within and outside the microgel. Furthermore, in the high frequency relaxation spectrum, heavy water outside the microgel (h1-process with a relaxation time of h1, τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h1</sub> , fixed as that of pure heavy water) and confined heavy water within the microgel (h2-process with a relaxation time of h2, τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h2</sub> ) were evaluated in view of the two-water model’s assumption and contribution. Under volume phase transition temperature (VPTT), τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h2</sub> is about 4 to 5 times larger than τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h1</sub> , and it does not change much even though the temperature is raised. However, τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">h2</sub> rapidly increases above VPTT from 7 to 14, which reveals that the dynamics of heavy water are severely constrained inside the shrunken state of the PNIPAM microgel. The obtained results are compared to the dynamics of pure water in PNIPAM microgels aqueous suspension to better understand the effect of deuterium substitution for hydrogen on the dynamics of heavy water inside and outside of PNIPAM microgels.

Anatomically Detailed Simulation of Human Torso

Many existing digital human models approximate the human skeletal system using rigid bodies connected by rotational joints. While the simplification is considered acceptable for legs and arms, it significantly lacks fidelity to model rich torso movements in common activities such as dancing, Yoga, and various sports. Research from biomechanics provides more detailed modeling for parts of the torso, but their models often operate in isolation and are not fast and robust enough to support computationally heavy applications and large-scale data generation for full-body digital humans. This paper proposes a new torso model that aims to achieve high fidelity both in perception and in functionality, while being computationally feasible for simulation and optimal control tasks. We build a detailed human torso model consisting of various anatomical components, including facets, ligaments, and intervertebral discs, by coupling efficient finite-element and rigid-body simulations. Given an existing motion capture sequence without dense markers placed on the torso, our new model is able to recover the underlying torso bone movements. Our method is remarkably robust that it can be used to automatically "retrofit" the entire Mixamo motion database of highly diverse human motions without user intervention. We also show that our model is computationally efficient for solving trajectory optimization of highly dynamic full-body movements, without relying any reference motion. Physiological validity of the model is validated against established literature.

Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

The selection of an appropriate measurement system for an inertial navigation system requires an analysis of the impact of sensor errors on the position and orientation determination accuracy to ensure that the selected solution is cost-effective and complies with the requirements. In the current literature, this problem is solved based on the navigation duration only by considering the time-dependent errors due to sensor bias and random walk parameters or by conducting numerous simulations. In the former case, oversimplifying the analysis will not allow accurate values to be determined, while the latter method does not provide direct insight into the emerging dependencies. In contrast, this article introduces an analytic approach with a detailed model. This article presents general formulas, also written in detail for the measurement system model adopted and various manoeuvres. Although general equations are complicated, the use of piecewise constant motion variables allow us to discern fragments of equations corresponding to individual error sources. The results confirm the effect the carouseling has on the reduction of navigation errors. The general formulas presented extend the potential to analyse the influence of the entire host vehicle motion, while the detailed formulas make dependencies between motion and navigational errors evident.

Informed pixel pushing: A new method of large-motion handling for phase-based optical flow

In this paper, a novel method is presented to increase the efficacy of phase-based optical flow (PBOF) in cases of simultaneous relevant super-pixel and sub-pixel motions. To date, PBOF performs well for sub-pixel motions of interest while measurement potential for super-pixel motion remains limited. Although current methods exist across the literature to handle irrelevant super-pixel motions otherwise obstructing sub-pixel extraction, they are typically aimed at removing the super-pixel motion. The proposed method does not assume irrelevancy, instead working to maintain the entire motion signal without resolution reduction or combined processing techniques. The objective of this work is to reframe the small motion assumption of optical flow through dynamic processing, steerable filters, and motion thresholds so that PBOF can accurately extract super-pixel motions – particularly large-scale translation and in-plane rotation – while still extracting sub-pixel motion. Proof of concept is presented through various synthetic test cases followed by experimental validation, all showing good agreement.

TouchRoller: A Rolling Optical Tactile Sensor for Rapid Assessment of Textures for Large Surface Areas.

Tactile sensing is important for robots to perceive the world as it captures the physical surface properties of the object with which it is in contact and is robust to illumination and colour variances. However, due to the limited sensing area and the resistance of their fixed surface when they are applied with relative motions to the object, current tactile sensors have to tap the tactile sensor on the target object a great number of times when assessing a large surface, i.e., pressing, lifting up, and shifting to another region. This process is ineffective and time-consuming. It is also undesirable to drag such sensors as this often damages the sensitive membrane of the sensor or the object. To address these problems, we propose a roller-based optical tactile sensor named TouchRoller, which can roll around its centre axis. It maintains being in contact with the assessed surface throughout the entire motion, allowing for efficient and continuous measurement. Extensive experiments showed that the TouchRoller sensor can cover a textured surface of 8 cm × 11 cm in a short time of 10 s, much more effectively than a flat optical tactile sensor (in 196 s). The reconstructed map of the texture from the collected tactile images has a high Structural Similarity Index (SSIM) of 0.31 on average when compared with the visual texture. In addition, the contacts on the sensor can be localised with a low localisation error, 2.63 mm in the centre regions and 7.66 mm on average. The proposed sensor will enable the fast assessment of large surfaces with high-resolution tactile sensing and the effective collection of tactile images.

Sampling-Based Planning for Retrieving Near-Cylindrical Objects in Cluttered Scenes Using Hierarchical Graphs

We present an incremental sampling-based task and motion planner for retrieving near-cylindrical objects, like bottle, in cluttered scenes, which computes a plan for removing obstacles to generate a collision-free motion of a robot to retrieve the target object. Our proposed planner uses a two-level hierarchy, including the first-level roadmap for the target object motion and the second-level retrieval graph for the entire robot motion, to aid in deciding the order and trajectory of object removal. We use an incremental expansion strategy to update the roadmap and retrieval graph from the collisions between the target object, the robot, and the obstacles, in order to optimize the object removal sequence. The performance of our method is highlighted in several benchmark scenes, including a fixed robotic arm in a cluttered scene with known obstacle locations and a scene, where locations of some objects or even the target object are unknown due to occlusions. Our method can also efficiently solve the high-dimensional planning problem of object retrieval using a mobile manipulator and be combined with the symbolic planner to plan complex multistep tasks. We deploy our method to a physical robot and integrate it with nonprehensile actions to improve operational efficiency. Compared to the state-of-the-art approaches, our method reduces task and motion planning time up to 24.6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> with a higher success rate, and still provides a near-optimal plan.

수직점프에서 팔 스윙형태가 점프높이에 미치는 영향

Purpose: The purpose of this study is to analyze the effect of the arm swing direction on the jump height during a vertical jump and to suggest an efficient arm swing pattern (ASP).BR Method: Ten infrared cameras including two force plates were used to analyze the jumping motion. The subjects of the research were 10 male university students. The experiment task was to jump as high as possible by swinging from front to back, from back to front, and fixing their arms without swinging. A 3D cinematography was performed, and biomechanical variables werea nalyzed by dividing the entire motion period into a braking phase and an accelerating phase to efficiently compare changes at ASP.BR Results: Among the three arm swings, the jump height and the verticavle locity increased the most just before the take-off when the arm swung from back to front, antdh e jump height tended to increase with the magnitude of the impulse. However, the duration of the brainkg and accelerating phases, joint angle, torque, and power of the lower extremity did not show any charcateristic results depending on the ASP. The work done by the lower extremity joint also did not show a significant difference in the change of the ASP.BR Conclusion: The swing from back to front is the most efficient ASP because it increases jump height and vertical velocity just before take-off. However, other biomechnaical variables do not show a clear difference even when the ASP is changed. In contrast to the hip andn akle joints, the knee joint continued to exhibit eccentric contraction even during the accelerating phase, and this characteristic is evident when the arm is fixed. The decrease in eccentric contraction of the knee joint during the arm swing in the accelerating phase can be positive in that it suppresses energy absorption in the vertical jump.

Biomac3D: 2D-to-3D Human Pose Analysis Model for Tele-Rehabilitation Based on Pareto Optimized Deep-Learning Architecture

The research introduces a unique deep-learning-based technique for remote rehabilitative analysis of image-captured human movements and postures. We present a ploninomial Pareto-optimized deep-learning architecture for processing inverse kinematics for sorting out and rearranging human skeleton joints generated by RGB-based two-dimensional (2D) skeleton recognition algorithms, with the goal of producing a full 3D model as a final result. The suggested method extracts the entire humanoid character motion curve, which is then connected to a three-dimensional (3D) mesh for real-time preview. Our method maintains high joint mapping accuracy with smooth motion frames while ensuring anthropometric regularity, producing a mean average precision (mAP) of 0.950 for the task of predicting the joint position of a single subject. Furthermore, the suggested system, trained on the MoVi dataset, enables a seamless evaluation of posture in a 3D environment, allowing participants to be examined from numerous perspectives using a single recorded camera feed. The results of evaluation on our own self-collected dataset of human posture videos and cross-validation on the benchmark MPII and KIMORE datasets are presented.

Analytical Nonlinear Observability Analysis for Spacecraft Autonomous Relative Navigation

Spacecraft autonomous relative navigation is widely required in the field of on-orbit services. In previous works, it has been shown that the monocular sequential images (MSIs) is a cost-effective autonomous relative navigation method. However, given the lack of size and initial orbit of noncooperative targets, the relative navigation system (RNS) with MSIs cannot ensure to estimate the entire relative motion states during the whole observation process. It is critical to perform an online observability analysis for RNS with MSIs to ensure autonomous relative motion estimation validity and accuracy. An analytical nonlinear observability analysis method is proposed in this article to improve the computational efficiency. We study the attributes of the relative orbit dynamics model and Lie algebra operations, and find that the observability matrix is only related to the limited states. The relationship among those states, rank, and the Frobenius norm of observability matrix is demonstrated, which simplify the observability criteria conditions and the degree measurements in analytical forms. In addition, based on the proposed method, we analyze the influence of the orbital manifolds on the observability degree of RNS with MSIs. Several suggestions are proposed for orbital manifolds detecting. The conclusion is a theoretical supplement to the past numerical research results. Finally, we implement the numerical simulations, and the current study’s findings verified the effectiveness of the proposed observability analysis method.

Calculation of Coulomb breakup cross sections using a new Coulomb dynamical polarization potential

A new method for calculating the Coulomb breakup of unstable neutron-rich isotopes at high energies is presented. The calculations employ the eikonal approximation and use a new Coulomb dynamical polarization potential (CDPP), calculated by solving the Schr\"odinger equation for the entire motion of the exotic projectile as a two-body cluster structure using the adiabatic approximation and incorporating excitations to the continuum. Calculations for some exotic isotopes are compared with Coulomb dissociation cross section data and found to be in good agreement.