Motion In Space Research Articles

A Framework for Demonstrating, Forecasting, and Explaining Topic Evolution by Analyzing Geometrical Motion of Topic Embeddings

Abstract Topic analysis aims to study topic evolution and trends in order to help researchers understand the process of knowledge evolution and creation. This paper develops a novel topic evolution analysis framework, which we use to demonstrate, forecast, and explain topic evolution from the perspective of the geometrical motion of topic embeddings generated by pretrained language models. Our dataset comprises approximately 15 million papers in the computer science field, with 7,000 “fields of study” to represent the topics. First, we demonstrated that over 80% of topics had undergone obvious motion in the semantic vector space, based on the hyperplane and its normal vector generated by a support vector machine. Subsequently, we verified the predictability of the motion based on three vector regression models by predicting topic embeddings. Finally, we employed a decoder to explain the predicted motion, whose forecast embeddings can capture about 50% of unseen topics. Our research framework shows that topic evolution can be analyzed via the geometrical motion of topic embeddings, and the semantic motion of old topics nurtures new topics. The current study opens new research pathways in topic analysis and sheds light on the topic evolution mechanism from a novel geometric perspective. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00344

Structural Design and Kinematic Analysis of Cable-Driven Soft Robot

Continuous robots have attracted more and more attention from the robotics community due to their high degree of flexibility and pliability, and have shown great potential for application in a variety of fields. With the continuous progress of material science, control technology, and artificial intelligence, the performance and application range of soft robotics have been further expanded, in which the cable drive has the advantages of large workspace, high flexibility, etc. The cable-driven soft robotic arm serves as an ultra-redundant robot that can operate in cramped and confined environments. In this paper, a cable-driven soft robot based on soft continuums and a cross gimbal is presented. The kinematics of the cable-driven soft robot is modeled and the mapping relations of the kinematics are solved by the D–H method and piecewise constant curvature, and the relations between the cable length, joint angle, and pose are further derived. Finally, the motion space of the cable-driven soft robot in the three-dimensional coordinate system is obtained by MATLAB2021b, and the single-segment soft body is simulated and analyzed using ADAMS to compare the theoretical data with the actual data and verify the reliability of this structure and method.

HiSC4D: Human-Centered Interaction and 4D Scene Capture in Large-Scale Space Using Wearable IMUs and LiDAR.

We introduce HiSC4D, a novel Human-centered interaction and 4D Scene Capture method, aimed at accurately and efficiently creating a dynamic digital world, containing large-scale indoor-outdoor scenes, diverse human motions, rich human-human interactions, and human-environment interactions. By utilizing body-mounted IMUs and a head-mounted LiDAR, HiSC4D can capture egocentric human motions in unconstrained space without the need for external devices and pre-built maps. This affords great flexibility and accessibility for human-centered interaction and 4D scene capturing in various environments. Taking into account that IMUs can capture human spatially unrestricted poses but are prone to drifting for long-period using, and while LiDAR is stable for global localization but rough for local positions and orientations, HiSC4D employs a joint optimization method, harmonizing all sensors and utilizing environment cues, yielding promising results for long-term capture in large scenes. To promote research of egocentric human interaction in large scenes and facilitate downstream tasks, we also present a dataset, containing 8 sequences in 4 large scenes (200 to 5,000 [Formula: see text]), providing 36 k frames of accurate 4D human motions with SMPL annotations and dynamic scenes, 31k frames of cropped human point clouds, and scene mesh of the environment. A variety of scenarios, such as the basketball gym and commercial street, alongside challenging human motions, such as daily greeting, one-on-one basketball playing, and tour guiding, demonstrate the effectiveness and the generalization ability of HiSC4D. The dataset and code will be publicly available for research purposes.

Multi-Degree-of-Freedom Platforms: Development and Outlook

Background: Multi-degree-of-freedom platforms are frequently employed in space docking devices, motion modeling, and robotics. Complex research is being done on multidegree- of-freedom platforms, including work on spatial route creation, control simulation, and forward and backward platform motion solutions. The development of research platforms in their current state is advantageous for advancing multi-degree-of-freedom motion research, which has the potential to advance numerous sectors through new technology. Objective: In this patent study, the benefits and drawbacks of various platforms are explored to analyze the development trend of platforms for academics and engineers through the most recent development of multi-degree-of-freedom platforms. Methods: By using the research methodology, research substance, and inventive structure of the most recent representative patents of the multi-degree-of-freedom platform, the platform's operating principle and characteristics are demonstrated. Results: By contrasting multi-degree-of-freedom platforms in various application domains, the issues with current multi-degree-of-freedom platforms are enumerated, and the platforms' potential future development path and research topics are suggested. Conclusion: The growth of the aviation, medical, and military industries is aided by the development of multi-degree-of-freedom platforms, and the flexible distribution of high-precision parallel platforms has promising future development.

Hidden-like Attractors in a Class of Discontinuous Dynamical Systems

In continuous dynamical systems, a hidden attractor occurs when its basin of attraction does not connect with small neighborhoods of equilibria. This research aims to investigate the presence of hidden-like attractors in a class of discontinuous systems that lack equilibria. The nature of non-smoothness in Filippov systems is critical for producing a wide variety of interesting dynamical behaviors and abrupt transient responses to dynamic processes. To show the effects of non-smoothness on dynamic behaviors, we provide a simple discontinuous system made of linear subsystems with no equilibria. The explicit closed-form solutions for each subsystem have been derived, and the generalized Poincaré maps have been established. Our results show that the periodic orbit can be completely established within a sliding region. We then carry out a mathematical investigation of hidden-like attractors that exhibit sliding-mode characteristics, particularly those associated with grazing-sliding behaviors. The proposed system evolves by adding a nonlinear function to one of the vector fields while still preserving the condition that equilibrium points do not exist in the whole system. The results of the linear system are useful for investigating the hidden-like attractors of flow behavior across a sliding surface in a nonlinear system using numerical simulation. The discontinuous behaviors are depicted as motion in a phase space governed by various hidden attractors, such as period doubling, period-m segments, and chaotic behavior, with varying interactions with the sliding mode.

MpcMech: Multi-Point Conjugation Mechanisms

A mechanism is an assembly of moving parts interconnected by joints to transfer an input motion to a desired output motion. Traditionally, to generate a complex motion, mechanisms are modeled by selecting and combining a number of mechanical parts with simple shapes such as links, gears, and cams. Combining multiple mechanical parts results in a mechanism with an intricate topology, which not only complicates assembly and maintenance but also deteriorates the functionality of generating motions due to accumulation of manufacturing imprecisions. To get rid of these limitations, we study mechanisms with a single pair of moving parts for generating complex motions. We model the pair of moving parts as a pair of conjugate surfaces with multiple conjugation points, forming a multi-point conjugation mechanism. To study this new mechanism, we establish a connection between conjugate surface pairs and form-closure grasps to formulate a dynamic form closure condition under which one conjugate surface is able to continuously transfer the motion to the other conjugate surface by utilizing multiple conjugation points. Guided by the condition, we propose an optimization-based approach to model the geometry of a multi-point conjugation mechanism for exactly generating a user-specified motion, in 1-, 2-, or 3-DOF motion space. The core of our approach is to model multiple conjugate curve pairs that satisfy various requirements in multi-point conjugation, dynamic form closure, and surface fabricability. We demonstrate the effectiveness of our approach by modeling different classes of multi-point conjugation mechanisms to generate various motions, evaluating the mechanisms' kinematic performance with 3D printed prototypes, and presenting three applications of these mechanisms.

Dynamical phase transitions in the XY model: A Monte Carlo and mean-field-theory study.

We investigate the dynamical phases and phase transitions arising in a classical two-dimensional anisotropic XY model under the influence of a periodically driven temporal external magnetic field in the form of a symmetric square wave. We use a combination of finite temperature classical Monte Carlo simulation, implemented within a CPU+GPU paradigm, utilizing local dynamics provided by the Glauber algorithm and a phenomenological equation-of-motion approach based on relaxational dynamics governed by the time-dependent free energy within a mean-field approximation to study the model. We investigate several parameter regimes of the variables (magnetic field, anisotropy, and the external drive frequency) that influence the anisotropic XY system. We identify four possible dynamical phases: Ising-SBO, Ising-SRO, XY-SBO, and XY-SRO. Both techniques indicate that only three of them (Ising-SRO, Ising-SBO, and XY-SRO) are stable dynamical phases in the thermodynamic sense. Within the Monte Carlo framework, a finite-size scaling analysis, shows that XY-SBO does not survive in the thermodynamic limit giving way to either an Ising-SBO or a XY-SRO regime. The finite-size scaling analysis further shows that the transitions between the three remaining dynamical phases either belong to the two-dimensional Ising universality class or are first-order in nature. Within the mean-field calculations yield three stable dynamical phases, i.e., Ising-SRO, Ising-SBO and XY-SRO, where the final steady state is independent of the initial condition chosen to evolve the equationsof motion, as well as a region of bistability where the system flows to either Ising-SBO or XY-SRO (Ising-SRO) depending on the initial condition. Unlike the stable dynamical phases, the XY-SBO represents a transient feature that is eventually lost to either Ising-SBO or XY-SRO. Our mean-field analysis highlights the importance of the competition between switching of the stationary point(s) of the free energy after each half cycle of the external field and the two-dimensional nature of the phase space for the equationsof motion.

Design of a Novel Macro-Micro Integrated Brain Surgery Robot Based on Modular Parallel Mechanisms

The advancement and development of medical surgical robots have provided new technological support for brain surgery and neurosurgical procedures, improving the reliability of highly complex and precise surgeries. In turn, this urges the design and development of novel surgical robots to possess higher precision, stability, and enhanced motion capabilities. In response to this practical demand, this paper introduces a macro-micro integrated medical brain surgery robot system based on the concept of modular PMs (parallel mechanisms), which have a total of 13 active DOFs (degrees of freedom). This system divides the motion process of brain surgery into a large-scale macro-motion space and a small-scale high-precision motion space for design and planning control. The introduction of the design concept that combines multiple modular parallel sub-mechanisms has brought a significant level of decoupling characteristics to the mechanism itself. A comprehensive introduction and analysis of the surgical robot are provided, covering aspects such as design, kinematics, motion planning, and performance indicators. To address the pose allocation and coordination of motion between the macro platform and the micro platform, a pose allocation algorithm based on the decoupling and non-decoupling characteristics in various dimensions of the macro-micro platform is proposed. The designed measurement experiments have demonstrated that the repeatability in positioning accuracy of the macro and micro platform reaches the level of micron and submicron respectively. Practical experiments of motion control and simulated brain electrode implantation validate the excellent performance and stability of the entire surgical robot system. This research contributes innovative insights to the development of medical surgical robot systems, particularly in the domain of mechanism design.

A Multi-Posture Grasping Manipulator Actuated by Shape Memory Alloy with Different Functional Modules.

Currently, multi-posture robots have complex grasping robotic manipulators with low power density, making it difficult to miniaturize and integrate. In this paper, a multi-posture grasping manipulator actuated by shape memory alloy with different functional modules is presented. It is composed of deflection, translation, rotation and grasping modules. Based on a D-H parameter method, the end motion trajectory model is established and the end motion space is drawn. Finally, the grasping experiment of a light circular object is carried out to verify the validity of the multi-posture grasping function of the multi-module combination manipulator, which provides a choice for future intelligent robot manipulators.

Achieving view-distance and -angle invariance in motion prediction using a simple network

Recently, human motion prediction has gained significant attention and achieved notable success. However, current methods primarily rely on training and testing with ideal datasets, overlooking the impact of variations in the viewing distance and viewing angle, which are commonly encountered in practical scenarios. In this study, we address the issue of model invariance by ensuring robust performance despite variations in view distances and angles. To achieve this, we employed Riemannian geometry methods to constrain the learning process of neural networks, enabling the prediction of invariances using a simple network. Furthermore, this enhances the application of motion prediction in various scenarios. Our framework uses Riemannian geometry to encode motion into a novel motion space to achieve prediction with an invariant viewing distance and angle using a simple network. Specifically, the specified path transport square-root velocity function is proposed to aid in removing the view-angle equivalence class and encode motion sequences into a flattened space. Motion coding by the geometry method linearizes the optimization problem in a non-flattened space and effectively extracts motion information, allowing the proposed method to achieve competitive performance using a simple network. Experimental results on Human 3.6M and CMU MoCap demonstrate that the proposed framework has competitive performance and invariance to the viewing distance and viewing angle.

Dynamic cluster field modeling of collective chemotaxis

Collective migration of eukaryotic cells is often guided by chemotaxis, and is critical in several biological processes, such as cancer metastasis, wound healing, and embryogenesis. Understanding collective chemotaxis has challenged experimental, theoretical and computational scientists because cells can sense very small chemoattractant gradients that are tightly controlled by cell-cell interactions and the regulation of the chemoattractant distribution by the cells. Computational models of collective cell migration that offer a high-fidelity resolution of the cell motion and chemoattractant dynamics in the extracellular space have been limited to a small number of cells. Here, we present Dynamic cluster field modeling (DCF), a novel computational method that enables simulations of collective chemotaxis of cellular systems with O(1000)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {O}}(1000)$$\\end{document} cells and high-resolution transport dynamics of the chemoattractant in the time-evolving extracellular space. We illustrate the efficiency and predictive capabilities of our approach by comparing our numerical simulations with experiments in multiple scenarios that involve chemoattractant secretion and uptake by the migrating cells, cell migration in confined spaces, regulation of the attractant distribution by cell motion, and interactions of the chemoattractant with an enzyme. The proposed algorithm opens new opportunities to address outstanding problems that involve collective cell migration in the central nervous system, immune response and cancer metastasis.

Collective coordinate models for 2-vortex shape mode dynamics

Models are developed for the motion of charge-2 Abelian Higgs vortices through the 2-vortex moduli space M, with the vortices excited by their shape mode oscillations. The models simplify to the well-known geodesic flow on M, modified by a potential, when the mode oscillations are fast relative to the moduli space motion and their amplitudes are small. When the lowest-frequency mode is excited with a large amplitude, the geodesic flow is not a correct description. Instead, a chaotic, or even fractal, multibounce structure in vortex-vortex collisions is predicted. Published by the American Physical Society 2024

Parameter study for hot spot trajectories around SgrA*

Context. Intense flaring events in the near-infrared and X-ray wavebands of our Galactic center have been the subject of research for decades. In recent years, the GRAVITY instrument of the Very Large Telescope captured the motion and polarimetric signature of such a flare in close proximity to the supermassive black hole. Aims. This study aims to investigate a broad parameter space for hot spot motion in the vicinity of SgrA* and reproduce the observed flaring behavior. Methods. To this end, we have developed a general relativistic radiative transfer code and conducted a parameter study including both planar and ejected hot spot configurations around supermassive black holes. Results. Super-Keplerian orbital frequencies are favored by circular equatorial, cylindrical and parabolic models, whereas conical hot spot trajectories provide a better fit for orbital frequencies below the Keplerian value. Additionally, a distant observer cannot effectively differentiate between Schwarzschild and Kerr black holes, as well as face-on orbits at different observation angles.

Brownian motion in a vector space over a local field is a scaling limit

For any natural number d, the Vladimirov–Taibleson operator is a natural analogue of the Laplace operator for complex-valued functions on a d-dimensional vector space V over a local field K. Just as the Laplace operator on L2(Rd) is the infinitesimal generator of Brownian motion with state space Rd, the Vladimirov–Taibleson operator on L2(V) is the infinitesimal generator of real-time Brownian motion with state space V. This study deepens the formal analogy between the two types of diffusion processes by demonstrating that both are scaling limits of discrete-time random walks on a discrete group. It generalizes the earlier works, which restricted V to be the p-adic numbers.

Design of a mixed robotic machining system and its application in support removal from metal additive manufactured thin-wall parts

Robotic machining could provide a solution for removing supports from metal additive manufactured workpieces, replacing labor-intensive work. However, the robot’s intrinsic weaknesses of low positioning accuracy and structural rigidity primarily restrict its applications. Improving the accuracy of robotic machining remains an unresolved issue. A mixed solution is proposed, in which a portable CNC machine with the capability of visual feature recognition is equipped with a universal industrial robot. The robot implements positioning motions in a large space, while the portable CNC fulfills accurate machining motions on a local feature of the workpiece. A sizeable weight of the portable CNC exerts a moderate load on the industrial robot’s joints, increasing joint stiffness. The mixed machining system exhibits high accuracy and stiffness when milling a steel/titanium alloy workpiece, achieving tolerances up to ±0.04 mm on a 60×80 mm U-shaped path without exciting any structural vibration modes. When the dimension of the workpiece exceeds the machining range of the portable CNC, a combined algorithm of coarse-fine registration based visual identification and robot error compensation is designed to align the spatial coordinates of the machining motion with that of the positioning motion, thereby extending the machining range with high accuracy. Through the proposed mixed robot machining method, experiments of doubling the machining range have been done to verify that the mixed machining robotic system is able to slot a 550 mm-long path with accuracy of ±0.1 mm. Furthermore, the mixed robotic machining system is applied to recognize and remove multiple supports of lattices, grids and ribs from a titanium-alloy additive manufactured thin-wall workpiece with high accuracy and high efficiency.

Evaluation on Numerical Method of Differential Formula Based on Optimal Control of Space Robot's Attitude and Motion

Evaluation on Numerical Method of Differential Formula Based on Optimal Control of Space Robot's Attitude and Motion

Group-theoretic analysis of symmetry-preserving deployable structures and metamaterials.

Many deployable structures in nature, as well as human-made mechanisms, preserve symmetry as their configurations evolve. Examples in nature include blooming flowers, dilation of the iris within the human eye, viral capsid maturation and molecular and bacterial motors. Engineered examples include opening umbrellas, elongating scissor jacks, variable apertures in cameras, expanding Hoberman spheres and some kinds of morphing origami structures. In these cases, the structures either preserve a discrete symmetry group or are described as an evolution from one discrete symmetry group to another of the same type as the structure deploys. Likewise, elastic metamaterials built from lattice structures can also preserve symmetry type while passively deforming and changing lattice parameters. A mathematical formulation of such transitions/deployments is articulated here. It is shown that if [Formula: see text] is Euclidean space, [Formula: see text] is a continuous group of motions of Euclidean space and [Formula: see text] is the type of the discrete subgroup of [Formula: see text] describing the symmetries of the deploying structure, then the symmetry of the evolving structure can be described by time-dependent subgroups of [Formula: see text] of the form [Formula: see text], where [Formula: see text] is a time-dependent affine transformation. Then, instead of considering the whole structure in [Formula: see text], a 'sector' of it that lives in the orbit space [Formula: see text] can be considered at each instant in time, and instead of considering all motions in [Formula: see text], only representatives from right cosets in the space [Formula: see text] need to be considered. This article is part of the theme issue 'Current developments in elastic and acoustic metamaterials science (Part 1)'.

Non-invasive measurement of wall shear stress in microfluidic chip for osteoblast cell culture using improved depth estimation of defocus particle tracking method.

The development of a non-invasive method for measuring the internal fluid behavior and dynamics of microchannels in microfluidics poses critical challenges to biological research, such as understanding the impact of wall shear stress (WSS) in the growth of a bone-forming osteoblast. This study used the General Defocus Particle Tracking (GDPT) technique to develop a non-invasive method for quantifying the fluid velocity profile and calculated the WSS within a microfluidic chip. The GDPT estimates particle motion in a three-dimensional space by analyzing two-dimensional images and video captured using a single camera. However, without a lens to introduce aberration, GDPT is prone to error in estimating the displacement direction for out-of-focus particles, and without knowing the exact refractive indices, the scaling from estimated values to physical units is inaccurate. The proposed approach addresses both challenges by using theoretical knowledge on laminar flow and integrating results obtained from multiple analyses. The proposed approach was validated using computational fluid dynamics (CFD) simulations and experimental video of a microfluidic chip that can generate different WSS levels under steady-state flow conditions. By comparing the CFD and GDPT velocity profiles, it was found that the Mean Pearson Correlation Coefficient is 0.77 (max = 0.90) and the Mean Intraclass Correlation Coefficient is 0.66 (max = 0.82). The densitometry analysis of osteoblast cells cultured on the designed microfluidic chip for four days revealed that the cell proliferation rate correlates positively with the measured WSS values. The proposed analysis can be applied to quantify the laminar flow in microfluidic chip experiments without specialized equipment.

Dynamical traceback age of the Octans young stellar association

Context. Octans is one of the most distant (d ∼ 150 pc) young stellar associations of the solar neighbourhood, and it has not yet been sufficiently explored. Its age is still poorly constrained in the literature and requires further investigation. Aims. We take advantage of the state-of-the-art astrometry delivered by the third data release of the Gaia space mission combined with radial velocity measurements obtained from high-resolution spectroscopy to compute the 3D positions and 3D spatial velocities of the stars and derive the dynamical traceback age of the association. Methods. We created a clean sample of cluster members by removing potential outliers from our initial list of candidate members. We then performed an extensive traceback analysis using different subsamples of stars, different metrics to define the size of the association, and different models for the Galactic potential to integrate the stellar orbits in the past. Results. We derive a dynamical age of $ 34^{+2}_{-2} $ Myr that is independent from stellar models and represents the most precise age estimate currently available for the Octans association. After correcting the radial velocity of the stars for the effect of gravitational redshift, we obtain a dynamical age of $ 33^{+3}_{-1} $ Myr, which is in very good agreement with our first solution. This shows that the effect of gravitational redshift is small for such a distant young stellar association. Our result is also consistent with the less accurate age estimates obtained in previous studies from lithium depletion (30–40 Myr) and isochrones (20–30 Myr). By integrating the stellar orbits in time, we show that the members of Octans and Octans-Near had different locations in the past, which indicates that the two associations are unrelated despite the close proximity in the sky. Conclusions. This is the first reliable and precise dynamical age result for the Octans young stellar association. Our results confirm that it is possible to derive precise dynamical ages via the traceback method for ∼30 Myr old stellar clusters at about ∼150 pc with the same precision level that has been achieved in other studies for young stellar groups within 50 pc of the Sun. This represents one more step towards constructing a self-consistent age scale based on the 3D space motion of the stars in the young stellar clusters of the solar neighbourhood.

Integrating Newton's equations of motion in the reciprocal space.

We here present the normal dynamics technique, which recasts the Newton's equations of motion in terms of phonon normal modes by exploiting a proper sampling of the reciprocal space. After introducing the theoretical background, we discuss how the reciprocal space sampling enables us to (i) obtain a computational speedup by selecting which and how many wave vectors of the Brillouin zone will be considered and (ii) account for distortions realized across large atomic distances without the use of large simulation cells. We implemented the approach into an open-source code, which we used to present three case studies: in the first one, we elucidate the general strategy for the sampling of the reciprocal space; in the second one, we illustrate the potential of the approach by studying the stabilization effect of temperature in α-uranium; and in the last one, we investigate the characterization of Raman spectra at different temperatures in MoS2/MX2 transition metal dichalcogenide heterostructures. Finally, we discuss how the procedure is general and can be used to simulate periodic, semiperiodic, and finite systems such as crystals, slabs, nanoclusters, or molecules.