Motion Generation Research Articles

A stochastic approach for the generation and combination of vertical and horizontal strong ground motion

Damage to structures during near-fault earthquakes often indicates that the vertical component was larger than what is usually considered in seismic design. Commonly, the vertical component of seismic ground motions is associated with the P-wave. In contrast, the horizontal seismic ground motions’ component is usually related to the arrival of the S-wave. However, findings of recent near-fault events indicate that both the horizontal and the vertical motions are a mixture of S and P-waves. Therefore, the need to generate three-component artificial accelerograms for structural design arises. This paper proposes a double aim: starting from the well-noted Snell’s law, a physical explanation of the mixture of S and P-waves is outlined. Then, a novel integrodifferential filter system for the stochastic simulation of the three components of strong motion is presented. The proposed study is applied to some theoretical applications as well as to two real Italian seismic events.

Carreau nanofluid dynamics with activation energy gyrotactic microorganisms in a porous medium: Application to solar energy

This study investigates the magnetohydrodynamic (MHD) flow of Carreau nanofluid through a porous medium with motile microorganisms, focusing on various geometries under shear-thinning and shear-thickening conditions. The aim is to elucidate how factors such as activation energy, Schmidt number, Peclet number, bioconvection, Brownian motion, thermophoresis, and heat generation influence flow dynamics. Using similarity transformations, we nondimensionalize the governing equations and solve them numerically with the Runge–Kutta method and a shooting technique in MATLAB. Our findings indicate that variations in Carreau, magnetic, and suction parameters notably impact velocity, temperature, concentration, diffusion, wall friction, and heat transfer, generally resulting in reduced values. Specifically, the flat plate geometry exhibits lower skin friction, heat transfer, and mass transfer rates, as well as decreased gyrotactic microorganism effects. Increased activation energy enhances concentration fields, signaling slower chemical reactions, while higher Peclet numbers and bioconvection inversely affect flow properties. Additionally, reduced Schmidt numbers lead to lower microorganism concentrations. These results provide valuable insights into the complex interactions between fluid dynamics and microorganism behavior, with implications for optimizing processes in biotechnology and environmental management.

Design and Performance Analysis of Robotic Vertebral-Disc Unit with Cable-Driven Mechanism.

The humanoid torso is crucial for the overall performance of a humanoid robot. Developing an effective humanoid spine is essential for enhancing this mechanism. This paper introduces a one-vertebral-disc unit inspired by human spine anatomy. A prototype was created using 3D-printed parts and commercially available components. Two general human-like motions are achieved using two servo motors and two pulleys, reducing the number of servo motors needed. The results indicate that a one-vertebral-disc unit can bend up to 15 degrees. The proposed mechanism functions effectively and successfully mimics human movements. It holds potential for integration into humanoid torsos, enabling efficient performance in human-like tasks in the future.

Light-regulated soliton dynamics in liquid crystals

Electrically powered solitons are particle-like field configurations in out-of-equilibrium nematics that have garnered significant interest. However, their random generation and lack of controllable motion have limited their application. Here, we present a reconfigurable optoelectronic approach capable of regulating the entire lifecycle of solitons by utilizing multi-strategy digital light projection to construct delicate patterning of virtual electrode. We demonstrate that optically actuated domains with diverse geometry enable the generation of multiple solitons and further allow in-situ formation of individual soliton by matching the light pattern to its dimension. Exquisitely engineered light intensity of patterns facilitates modulation of soliton velocity and transformation of propagating direction. The utilization of a light-guided channel enables the on-demand control of soliton trajectories along customized paths. Furthermore, dynamic light patterns that vary in space and time allow for collective motion such as migration, mimicking phototaxis in biological systems. This reconfigurable manipulation strategy, grounded in the photoconductive effect, proves highly versatile and effective in directing soliton dynamics, heralding the potential for their programmable control and offering a significant advantage in multitasking scenarios.

Motion Planning for Dynamic Three-Dimensional Manipulation for Unknown Flexible Linear Object

Generally, deformable objects have large and nonlinear deformations. Because of these characteristics, recognition and estimation of their movement are difficult. Many studies have been conducted aimed at manipulating deformable objects at will. However, they have been focused on situations wherein a rope’s properties are already known from prior experiments. In our previous work, we proposed a motion planning algorithm to manipulate unknown ropes using a robot arm. Our approach considered three steps: motion generation, manipulation, and parameter estimation. By repeating these three steps, a parameterized flexible linear object model that can express the actual rope movements was estimated, and manipulation was realized. However, our previous work was limited to 2D space manipulation. In this paper, we extend our previously proposed method to address casting manipulation in a 3D space. Casting manipulation involves targeting the flexible linear object tips at the desired object. While our previous studies focused solely on two-dimensional manipulation, this work examines the applicability of the same approach in 3D space. Moreover, 3D manipulation using an unknown flexible linear object has never been reported for dynamic manipulation with flexible linear objects. In this work, we show that our proposed method can be used for 3D manipulation.

Dynamical Properties of Perturbed Hill’s System

In this work, some dynamical properties of Hill’s system are studied under the effect of continued fraction perturbation. The locations and kinds of equilibrium points are identified, and it is demonstrated that these points are saddle points and the general motion in their proximity is unstable. Furthermore, the curves of zero velocity and the regions of possible motion are defined at different Jacobian constant values. It is shown that the regions of forbidden motion increase with increasing Jacobian constant values and there is a noticeable decrease in the permissible regions of motion, leading to the possibility that the body takes a path far away from the primary body and escapes to take an unknown trajectory. Furthermore, the stability of perturbed motion is analyzed from the perspective of a linear sense, and it is observed that the linear motion is also unstable.

Morphometric and morphostructural analysis as a modeling tool in mass movement scenarios (Bucaramanga, Colombia)

The basin is its own environment and sensitive to changes of both natural origin (endogenous and exogenous) and anthropic factors. Due to these changes, especially those of natural origin, basins shape their surfaces by adapting them to these effects, which gives rise to an intrinsic dynamic development that leads in some instances to morphodynamic processes, especially in the generation of mass movements. In order to establish, from the structure of the basin, the magnitude and patterns of these changes, a series of morphometric analyses are carried out within the tectonic context evaluated by the geometry of the basin as a function of mass movements. Analysis that has a cartographic basis at a scale of 1:25,000 and that describes these conditions that can be extrapolated to other regions due to the versatility in the implementation of the method and its methodology. From the analysis carried out, it was observed that morphometric parameters, especially those related to an oblong and/or elongated shape, are those that define the basin with a high sensitivity in the degree of susceptibility to mass movements. At the same time, parameters such as slope (30° to 40°) and relative relief (400 m to 500 m) sector the regions within the basin where high susceptibility is generated. From these analyses, proposals such as the one designed in this study can be constructed that respond to these characteristics of the basins as a function of mass movements and that are easily applicable in other regions.

Generation of synthetic spectrum-compatible bi-directional ground motions with specific directionality

Ground motions compatible with the maximum-direction response spectrum (RotD100) condition are emphasized in performance-based design and seismic risk assessment of civil structures in different regions. Due to the complex nature and uncertainty of earthquakes, the comprehensive inclusion of essential characteristics of ground motions is crucial. Recently, the directionality effect of horizontal bi-directional ground motions, representing the variation of the response spectral ordinate amplitude along various directions, on the seismic performance assessment of certain structures or key structural elements has received increasing attention in seismic analysis. However, from the seismic design perspective, there is still a lack of a method that can generate bi-directional ground motions comprehensively reflecting the directionality effect. This study focuses on the correction of ground motion directionality when generating synthetic bi-directional ground motions for a given target response spectrum. An efficient and integrated algorithm is proposed. To demonstrate the applicability of the proposed algorithm, three different target RotD100 response spectra are determined according to modern seismic design codes, and 20 pairs of bi-directional ground motions are generated using the proposed algorithm for each target spectrum. It is shown that with the proposed algorithm, the generated motions present a close match to the target RotD100 response spectrum and meet the specific directionality requirement. In addition, due to the iterative modification of the envelope function, the energy of the generated ground motion is also consistent with the scaled natural records.

A posture subspace in primary motor cortex.

To generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1's activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures. We found that posture- and goal-related components of neural population activity were separable and resided in nearly orthogonal subspaces. The posture subspace was stable across tasks. Within each task, neural trajectories for each goal had similar shapes across postures. Our results reveal a simpler organization of posture information in M1 than previously recognized. The compartmentalization of posture and goal information might allow the two to be flexibly combined in the service of our broad repertoire of actions.

Altered brain function during movement programming is linked with motor deficits after stroke: a high temporal resolution study.

Stroke leads to motor deficits, requiring rehabilitation therapy that targets mechanisms underlying movement generation. Cortical activity during the planning and execution of motor tasks can be studied using EEG, particularly via the Event Related Desynchronization (ERD). ERD is altered by stroke in a manner that varies with extent of motor deficits. Despite this consensus in the literature, defining precisely the temporality of these alterations during movement preparation and performance may be helpful to better understand motor system pathophysiology and might also inform development of novel therapies that benefit from temporal resolution. Patients with chronic hemiparetic post-stroke (n = 27; age 59 ± 14 years) and age-matched healthy right-handed control subjects (n = 23; 59 ± 12 years) were included. They performed a shoulder rotation task following the onset of a stimulus. Cortical activity was recorded using a 256-electrode EEG cap. ERD was calculated in the beta frequency band (15-30 Hz) in ipsilesional sensorimotor cortex, contralateral to movement. The ERD was compared over time between stroke and control subjects using permutation tests. The correlation between upper extremity motor deficits (assessed by the Fugl-Meyer scale) and ERD over time was studied in stroke patients using Spearman and permutation tests. Patients with stroke showed on average less beta ERD amplitude than control subjects in the time window of -350 to 50 ms relative to movement onset (t(46) = 2.8, p = 0.007, Cohen's d = 0.31, 95% CI [0.22: 1.40]). Beta-ERD values correlated negatively with the Fugl-Meyer score during the time window -200 to 400 ms relative to movement onset (Spearman's r = -0.54, p = 0.003, 95% CI [-0.77 to -0.18]). Our results provide new insights into the precise temporal changes of ERD after hemiparetic stroke and the associations they have with motor deficits. After stroke, the average amplitude of cortical activity is reduced as compared to age-matched controls, and the extent of this decrease is correlated with the severity of motor deficits; both were true during motor programming and during motor performance. Understanding how stroke affects the temporal dynamics of cortical preparation and execution of movement paves the way for more precise restorative therapies. Studying the temporal dynamics of the EEG also strengthens the promising interest of ERD as a biomarker of post-stroke motor function.

Shock-induced nanoscale pore collapse and hotspot in cyclotetramethylene tetranitramine (HMX)

Pore collapse induced hotspot formation is a key mechanism for initiating detonation of shocked high explosives. Accurate continuum models that faithfully capture the pore collapse dynamics and resulting hotspot temperatures for multiscale initiation of high explosive are still lacking. Here, an atomistically informed dislocation plasticity model is developed for cyclotetramethylene tetranitramine (HMX), which includes nonlinear thermoelasticity, pressure-dependent and temperature-dependent dislocation motion and homogeneous dislocation nucleation, and new melting criteria. Nanoscale pore collapse simulations based on the proposed model could well reproduce the pore collapse transition from a strength-dominated regime to a hydrodynamic regime observed in molecular dynamics results. During the pore collapse transition, dislocation motion and dislocation generation induced plasticity is decoupled and evaluated. It indicates that the homogeneous dislocation nucleation suppresses the dislocation motion. Through linkage analysis of dislocation physical quantity histories of tracer particles, this work clarifies the interplay between physical dependences and dislocation mechanisms on pore collapse behaviors for the first time. The results reveal that the transition of pore collapse regime emerges from the strong pressure-dependent homogeneous dislocation nucleation. In addition, the pore collapse responses and energy localizations of the proposed model are further compared with different strength models to prove the importance of pressure dependence and homogeneous dislocation nucleation on pore collapse behaviors. Based on the simulations of pore collapse, the potential heat sources are quantified to provide a physical understanding of hotspot formation mechanisms. The present work demonstrates a key step in multiscale modeling of high explosive initiation in that atomistic simulation results are directly used to guide and refine the mesoscale model of energetic crystal used in the continuum.

Joint angle synergy-based humanoid robot motion generation with fascia-inspired nonlinear constraints

AbstractWhen generating simultaneous joint movements of a humanoid with multiple degrees of freedom to replicate human-like movements, the approach of joint synergy can facilitate the generation of whole-body robotic movement with a reduced number of control inputs. However, the trade-off of minimizing control inputs and keeping characteristics of movements makes it difficult to improve movement performance in a simple control manner. In this paper, we introduce an approach by connecting and constraining these joints. It is inspired by the fascia network of the human body, which constrains the whole-body movements of a human. Compared to when only joint synergy is used, the effectiveness of the proposed method is verified by calculating the errors of joint positions of generated movements and human movements. The paper provides a detailed exploration of the proposed method, presenting simulation-experimental results that affirm its effectiveness in generated movements that closely resemble human movements. Furthermore, we provide one possible method on how these concepts can be implemented in actual robotic hardware, offering a pathway to improve movement control in humanoid robots within their mechanical limitations.

A Distributed Varying-Parameter Recurrent Neural Network for Solving the Motion Generation Problem of a Multimanipulator Collaborative System

A Distributed Varying-Parameter Recurrent Neural Network for Solving the Motion Generation Problem of a Multimanipulator Collaborative System

Analysis of heat generation impact on nanofluid flow over a stretching sheet

In this paper, studied the impact of heat generation of Nanofluid movement over a stretching sheet by the consideration of Thermophoresis, Brownian motion & first order chemical react parameters etc. Constructed the modelling equations with based on assumptions and by introducing emerging parameters. The equations converted to third order ODE through stream functions. FDM with collocation polynomial technique (bvp4c) employed to solve those equations through MATLAB software. The results are presented through graphical form with the influence of emerging parameters. Thickness of thermal boundary stratum decreased as enhancing of Prandtl number. Influence of Brownian motion parameter, fluid temperature raised and fall down the concentration. Temperature of fluid and concentration raised as enhancement of thermophoresis. A decrease in the heat transfer rate and an increase in the mass transfer rate are observed as thermophoresis, Brownian motion, and heat generation parameter values increasing. The enhancement of chemical reaction parameters intensifies the driving forces of temperature and concentration gradients, which govern heat and mass transfer, leading to increased rates of both heat and mass transfer. Validation of the model presented and the present results align well by past reported studies. This model can extent to analyse the hybrid nanofluid in the manufacturing process of detergent, painting and lubricants, analysis of blood flow in artery etc.

OpenSim Moco tracking simulations efficiently replicate predictive simulation results across morphologically diverse shoulder models

OpenSim Moco enables solving for an optimal motion using Predictive and Tracking simulations. However, Predictive simulations are computationally prohibitive, and the efficacy of Tracking in deviating from its reference is unclear. This study compares Tracking and Predictive approaches applied to the generation of morphology-specific motion in statistically-derived musculoskeletal shoulder models. The signal analysis software, CORA, determined mean correlation ratings between Tracking and Predictive solutions of 0.91 ± 0.06 and 0.91 ± 0.07 for lateral and forward-reaching tasks. Additionally, Tracking provided computational speed-up of 6–8 times. Therefore, Tracking is an efficient approach that yields results equivalent to Predictive, facilitating future large-scale modelling studies.

Simultaneous close-contact melting on two asymmetric surfaces: Demonstration, modeling and application to thermal storage

The present study deals with melting in a geometry suitable for Latent-Heat Thermal Energy Storage (LHTES) systems, which are of importance for future industrial installations utilizing solar energy or waste heat. The intrinsically high thermal resistance of phase-change materials (PCM) can be remedied by taking advantage of close contact melting (CCM), where the solid phase is separated from a hot surface by only a thin liquid layer. The basic CCM takes place on a horizontal flat surface, but during the last decade its application in various finned LHTES units has been demonstrated experimentally and analyzed numerically.Specifically, the configuration studied in the present work is relevant to a horizontal double-pipe concentric storage unit with a longitudinally finned inner tube. While this rather simple geometry has been extensively studied in the past, the present work is completely novel in its demonstration and analysis of simultaneous close-contact melting on two generally asymmetric surfaces created by the longitudinal fins. A unique experimental apparatus is introduced, based on the so-called 'Mercedes' configuration of the fins. It is designed transparent, allowing for real-time observation of melting sequences. Close-contact melting is achieved by supplying heat to the outer shell of the unit: the solid phase is detached from the shell and moves, by translation and rotation, in the liquid phase. The results from these experiments demonstrate the feasibility of CCM on two asymmetric walls within this system, hinting at the potential for optimizing the melting rate by utilizing a larger portion of the extended surface for CCM.A key component of this study is the development of a reliable numerical approach, which goes beyond the limitations of widely-applied enthalpy-porosity method and combines the general enthalpy formulation, convective heat transfer and general rigid body motion that includes rotation. Therefore, a new numerical model has been devised, using an in-house code realized in MATLAB. A full set of the governing conservation equations is solved using a finite-difference framework, integrated with advanced numerical methods for the fluid-solid interaction and an enthalpy formulation for the phase change process. The model is validated carefully, and then numerical studies are conducted to elucidate the melting process.The present paper presents a further proof of the special role that close-contact melting (CCM) can play in properly designed thermal energy storage units and finned systems in general. It is demonstrated that the fins, when properly designed and oriented, can induce CCM in their vicinity, contributing to a very significant increase in the melting rate, which reflects charging of the unit.

Categorical Codebook Matching for Embodied Character Controllers

Translating motions from a real user onto a virtual embodied avatar is a key challenge for character animation in the metaverse. In this work, we present a novel generative framework that enables mapping from a set of sparse sensor signals to a full body avatar motion in real-time while faithfully preserving the motion context of the user. In contrast to existing techniques that require training a motion prior and its mapping from control to motion separately, our framework is able to learn the motion manifold as well as how to sample from it at the same time in an end-to-end manner. To achieve that, we introduce a technique called codebook matching which matches the probability distribution between two categorical codebooks for the inputs and outputs for synthesizing the character motions. We demonstrate this technique can successfully handle ambiguity in motion generation and produce high quality character controllers from unstructured motion capture data. Our method is especially useful for interactive applications like virtual reality or video games where high accuracy and responsiveness are needed.

MoConVQ: Unified Physics-Based Motion Control via Scalable Discrete Representations

In this work, we present MoConVQ, a novel unified framework for physics-based motion control leveraging scalable discrete representations. Building upon vector quantized variational autoencoders (VQ-VAE) and model-based reinforcement learning, our approach effectively learns motion embeddings from a large, unstructured dataset spanning tens of hours of motion examples. The resultant motion representation not only captures diverse motion skills but also offers a robust and intuitive interface for various applications. We demonstrate the versatility of MoConVQ through several applications: universal tracking control from various motion sources, interactive character control with latent motion representations using supervised learning, physics-based motion generation from natural language descriptions using the GPT framework, and, most interestingly, seamless integration with large language models (LLMs) with in-context learning to tackle complex and abstract tasks.

A New Latin Hypercube Sampling with Maximum Diversity Factor for Reliability-Based Design Optimization of HLM

This research paper presents a new Latin hypercube sampling method, aimed at enhancing its performance in quantifying uncertainty and reducing computation time. The new Latin hypercube sampling (LHS) method serves as a tool in reliability-based design optimization (RBDO). The quantification technique is termed LHSMDF (LHS with maximum diversity factor). The quantification techniques, such as Latin hypercube sampling (LHS), optimum Latin hypercube sampling (OLHS), and Latin hypercube sampling with maximum diversity factor (LHSMDF), are tested against mechanical components, including a circular shaft housing, a connecting rod, and a cantilever beam, to evaluate its comparative performance. Subsequently, the new method is employed as the basis of RBDO in the synthesis of a six-bar high-lift mechanism (HLM) example to enhance the reliability of the resulting mechanism compared to Monte Carlo simulation (MCS). The design problem of this mechanism is classified as a motion generation problem, incorporating angle and position of the flap as an objective function. The six-bar linkage is first adapted to be a high-lift mechanism (HLM), which is a symmetrical device of the aircraft. Furthermore, a deterministic design, without consideration of uncertainty, may lead to unacceptable performance during the manufacturing step due to link length tolerances. The techniques are combined with an efficient metaheuristic known as teaching–learning-based optimization with a diversity archive (ATLBO-DA) to identify a reliable HLM. Performance testing of the new LHSMDF reveals that it outperforms the original LHS and OLHS. The HLM problem test results demonstrate that achieving optimum HLM with high reliability necessitates precision without sacrificing accuracy in the manufacturing process. Moreover, it is suggested that the six-bar HLM could emerge as a viable option for developing a new high-lift device in aircraft mechanisms for the future.

Motion generation for a tracked robot going over an unfixed obstacle on a slope using reinforcement learning

Tracked robots are useful in disaster recovery missions owing to their high traversability. However, even tracked robots find traversing terrains with obstacles such as rocks difficult. Particularly, unfixed obstacles pose problems. Therefore, this study aims to generate motion for tracked robots to go over unfixed obstacles on slopes by utilizing a reinforcement learning (RL) approach. In RL, rewards are important to make robots learn optimal policies for various tasks. Hence, a new definition of going over an unfixed obstacle is proposed. Based on the proposed definition, a sparse reward is designed to motivate the robot to go over the obstacle while avoiding the large sliding-down phenomenon responsible for the failure of going over and the large directional deviation of the robot. In our experiment, a robot is trained in a dynamic simulator and it attempts to go over a spherical unfixed obstacle under various environmental conditions: radius of the obstacle, slope degree, and initial position of the obstacle. We verify that the success rate converges to a high value and the robot successfully generates motions to go over the spherical unfixed obstacle.