Velocity Of Object Research Articles

Intelligent 3D Perception System for Semantic Description and Dynamic Interaction

This work proposes a novel semantic perception system based on computer vision and machine learning techniques. The main goal is to identify objects in the environment and extract their characteristics, allowing a dynamic interaction with the environment. The system is composed of a GPU processing source and a 3D vision sensor that provides RGB image and PointCloud data. The perception system is structured in three steps: Lexical Analysis, Syntax Analysis and finally an Analysis of Anticipation. The Lexical Analysis detects the actual position of the objects (or tokens) in the environment, through the combination of RGB image and PointCloud, surveying their characteristics. All information extracted from the tokens will be used to retrieve relevant features such as object velocity, acceleration and direction during the Syntax Analysis step. The anticipation step predicts future behaviors for these dynamic objects, promoting an interaction with them in terms of collisions, pull, and push actions. As a result, the proposed perception source can assign relevant information to mobile robots, not only about distances as traditional sensors, but about other environment characteristics and object behaviors. This novel perception source introduces a new class of skills to mobile robots. Experimental results obtained with a real robot are presented, showing the proposed perception source efficacy and potential.

Megahertz x-ray microscopy at x-ray free-electron laser and synchrotron sources

Modern emerging technologies, such as additive manufacturing, bioprinting, and new material production, require novel metrology tools to probe fundamental high-speed dynamics happening in such systems. Here we demonstrate the application of the megahertz (MHz) European X-ray Free-Electron Laser (EuXFEL) to image the fast stochastic processes induced by a laser on water-filled capillaries with micrometer-scale spatial resolution. The EuXFEL provides superior contrast and spatial resolution compared to equivalent state-of-the-art synchrotron experiments. This work opens up new possibilities for the characterization of MHz stochastic processes on the nanosecond to microsecond time scales with object velocities up to a few kilometers per second using XFEL sources.

CCD Optical Tomography System to Detect Solid Contamination in Crystal-Clear Water

The existence of foreign objects in crystal-clear water in beverage industries may cause major safety and health issues. The current observation of solid contamination such as X-ray and metal detector involves hazardous radiation. Some of the sensors applied intrusive and invasive techniques. This may cause the instability of the process flow. Therefore, this paper aims to develop a noninvasive and nonintrusive charge-coupled device optical tomography (CCD OPT) system to detect solid contamination in crystal-clear water. Investigations on three different opacity levels of objects, opaque, translucent, and transparent, are involved. The first experiment investigates the velocity and acceleration of the free-falling object. It is conducted to validate the accuracy of the system to detect the appearance of foreign object. The experiment result indicated that the system reached 82% accuracy. The second experiment reconstructs cross-sectional image of the process flow. The image reconstruction results are analyzed using the area error (AE) method. The image reconstruction AE range is between 0.0372 and 0.7269. The AE results show that the system has the capability to detect different opacity of objects which exist in crystal-clear water. Both experiments prove that the CCD OPT system is able to detect solid contamination in crystal-clear water.

Measurement of the rotational sense and velocity of an object using OAM wave in the radio‐frequency band

A method is presented to improve the determination of the rotational velocity of an on-axis spinning object. It uses the Orbital Angular Momentum (OAM) of an electromagnetic wave at 2.47 GHz, and measures the rotational Doppler frequency shift of a reflected wave. From this shift, the rotational velocity and the direction of rotation can be directly estimated with very good accuracy.

Evaluation of the fragmentation of an oxide-silicate material by image analysis

The study of the fragmentation parameters of non-metal objects, usually oxide-silicate, when colliding with metal barriers at various speeds is an important aspect of ensuring and assessing the reliability of the structure in aviation and space engineering, as they help simulate collision situations with striking objects in the air and space. With such an assessment, the size and number of fracture fragments are determined, as well as their speed and direction of movement at the moment of impact and after it. The problem of estimating the physical parameters of fracture fragments, such as size and weight, has been solved quite well, however, these methods are quite laborious. Evaluation of the speed and direction of movement of the fracture fragments is carried out, as a rule, when analysing the video recording of an experiment. The quality and information content of such an assessment depends on the quality of the video, shooting parameters and processing method. The paper proposes to use the image analysis implemented by using open source software ImageJ-Fiji for video processing and for estimating the parameters of fracture fragments. The paper discusses the experimental data on the impact of a spherical object of an oxide-silicate composition with a diameter of 23 mm with a static barrier - a sheet of titanium alloy 2 mm thick at a speed of 230 m/s. It is shown that using image analysis and statistical data processing, parameters such as the size and number of fracture fragments, the initial and final velocities of objects moving, as well as the direction of their movement can be set.

A high precision signal processing method for laser Doppler velocimeter

Fast Fourier transform (FFT) is commonly adopted as the signal processing method of laser Doppler velocimeter (LDV) system to get Doppler frequency which is the key factor of the calculation of object velocity. However, precision of FFT is restricted by phenomena caused by asynchronous sampling, such as spectral interference, fence effect and spectrum leakage. Aiming at enhancing the precision of LDV signal processing, an algorithm based on the association of spectral refinement and interpolation is put forward. Zoom-FFT was utilized to refine the local range of Doppler frequency estimated by FFT. The refined spectrum was further corrected by Rife-Vincent (Ⅲ) window interpolation and got the accurate estimate of Doppler frequency. Cubic spline fitting was applied to calculate the interpolation coefficient of Rife-Vincent (Ⅲ) window without solving a quintic equation in the computing procedure of interpolation. For experimental signals, the minimum relative error of proposed method is 0.02%. And for simulated signals, the minimum relative error reaches only 0.0013%. The proposed method has capability to significantly improve the precision of signal processing and is applicable for a LDV system.

Real-Time Fall Detection Using Microwave Doppler Sensor—Computational Cost Reduction Method Based on Genetic Algorithm

The risk of falling is a serious problem for the elderly. If the fall remains undetected for a considerable period, hypothermia and dehydration may occur, leading to death. Therefore, real-time detection of falls is critical. We previously proposed a fall-detection system based on a microwave Doppler sensor, which can capture the object's velocity. Our system performs template matching based on the dynamic time warping distance; hence, the processing time depends on the number of template datasets. Herein, we attempt a real-time fall detection by reducing the number of templates. We apply the genetic algorithm to select better templates. The fitness of the selected templates is evaluated by dividing the accuracy by the number of templates.

Analysis of students’ misconceptions on mechanics using three-tier diagnostic test and clinical interview

Students’ misconceptions analysis on mechanics had been done with qualitative approach. Data were obtained through a Three-tier Diagnostic Test adopted from the Force Concept Inventory Test and combined with the Certainly of Response Index of Saleem Hasan, and a clinical interview. Data is validated in three ways, namely the triangulation technique, using reference material, and member check. Then the data is analyzed through data reduction, data presentation, and conclusion. The results showed that misconceptions occurred in almost all the concepts. Misconceptions occur most often in the concepts of the object velocity in the Accelerated Linear Motion and the object motion in a parabolic trajectory. Factors that cause misconceptions mostly come from associative thinking, incomplete or wrong reasoning, and wrong intuition. Through clinical interviews, results were obtained that misconceptions were also influenced by the learning of teachers, instructional textbooks, internet, films, and the daily experiences of the students.

On the stability of trajectories in the task of pursuit

In two-dimensional and three-dimensional statements, a generalization of the pursuit problem is considered, when the object being pursued moves in a circle (plane case) or in a helical line (three-dimensional case), and various cases of dependence of object velocities in the problem are considered. Conditions are analytically obtained for the stability of the trajectories of motion of objects in the problem. Possible realization of this problem - the pursuit of one drone by another one as flying objects.

Newton’s Parabola Observed from Pappus’ Directrix, Apollonius’ Pedal Curve (Line), Newton’s Evolute, Leibniz’s Subtangent and Subnormal, Castillon’s Cardioid, and Ptolemy’s Circle (Hodograph) (09.02.2019)

Johannes Kepler and Isaac Newton inspired generations of researchers to study properties of elliptic, hyperbolic, and parabolic paths of planets and other astronomical objects orbiting around the Sun. The books of these two Old Masters “Astronomia Nova” and “Principia…” were originally written in the geometrical language. However, the following generations of researchers translated the geometrical language of these Old Masters into the infinitesimal calculus independently discovered by Newton and Leibniz. In our attempt we will try to return back to the original geometrical language and to present several figures with possible hidden properties of parabolic orbits. For the description of events on parabolic orbits we will employ the interplay of the directrix of parabola discovered by Pappus of Alexandria, the pedal curve with the pedal point in the focus discovered by Apollonius of Perga (The Great Geometer), and the focus occupied by our Sun discovered in several stages by Aristarchus, Copernicus, Kepler and Isaac Newton (The Great Mathematician). We will study properties of this PAN Parabola with the aim to extract some hidden parameters behind that visible parabolic orbit in the Aristotelian World. In the Plato’s Realm some curves carrying hidden information might be waiting for our research. One such curve - the evolute of parabola - discovered Newton behind his famous gravitational law. We have used the Castillon’s cardioid as the curve describing the tangent velocity of objects on the parabolic orbit. In the PAN Parabola we have newly used six parameters introduced by Gottfried Wilhelm Leibniz - abscissa, ordinate, length of tangent, subtangent, length of normal, and subnormal. We have obtained formulae both for the tangent and normal velocities for objects on the parabolic orbit. We have also obtained the moment of tangent momentum and the moment of normal momentum. Both moments are constant on the whole parabolic orbit and that is why we should not observe the precession of parabolic orbit. We have discovered the Ptolemy’s Circle with the diameter a (distance between the vertex of parabola and its focus) where we see both the tangent and normal velocities of orbiting objects. In this case the Ptolemy’s Circle plays a role of the hodograph rotating on the parabolic orbit without sliding. In the Plato’s Realm some other curves might be hidden and have been waiting for our future research. Have we found the Arriadne’s Thread leading out of the Labyrinth or are we still lost in the Labyrinth?

ЗАДАЧА ПРЕСЛЕДОВАНИЯ ОБЪЕКТА С ПОВЕРХНОСТИ, РАСПОЛОЖЕННОЙ НАД ПОВЕРХНОСТЬЮ ПРЕСЛЕДУЕМОГО А.А.

The purpose of this article is to describe a mathematical model of the pursuit problem in the case when the pursued and pursuing objects move along different surfaces placed one above the other. Orthonormal dynamic bases, which are determined by the vectors of velocities and normals to the surfaces, are introduced on the surfaces under consideration at the points where objects are located, and the construction of tangent planes is performed. Coordinates of our model's opponent are projected onto each specified plane for analysis and decision making. Velocities of objects in the model are constant in their magnitude. Inertness of objects is modeled using the angular velocity of rotation, which is essential in the described model. As a result of the research, an iterative algorithm leading to achievement of the threshold value in the horizontal plane of projections has been obtained. According to the research results, a dynamic visualization of the pursuit task has been made, which provides visibility to the results obtained.

Planetary Defense – Scientific and Technology Background

Near-Earth Objects: There are many objects in space that come close to earth's orbit. The velocities of asteroids or other near-earth objects (NEOs) that the National Aeronautics and Space Administration (NASA) and other in the international community are examining are about seventeen kilometers a second—the energy releases are equivalent to the detonation of a nuclear weapon. NEOs that are of concern, “potentially hazardous objects,” are ones where their orbits bring them into five million miles of Earth's orbit. NASA and other observatories around the world are constantly scanning the skies for potentially hazardous “near-Earth objects,” and thousands have already been found. At the start of 2019, the number of discovered near-Earth asteroids totaled more than 19,000. An average of thirty new discoveries are added each week. NASA estimates that at least 17,000 big near-Earth asteroids have yet to be discovered.

Anomaly Detection in Videos Using Optical Flow and Convolutional Autoencoder

Today, public areas, such as airports, hospitals, city centers are monitored by surveillance systems. The widespread use of surveillance systems reduces security concerns while creating an amount of video data that cannot be examined by people in real-time. Therefore, the concept of automatic understanding of video activities has raised the standards of security camera systems. In this paper, we propose a framework (OF-ConvAE-LSTM) to detect anomalies using Convolutional Autoencoder and Convolutional Long Short-Term Memory in an unsupervised manner. Besides the deep learning model, the feature extraction stage based on dense optical flow is applied in the framework to obtain the velocity and direction information of foreground objects. The experiments were carried out on three popular public datasets consisting of Avenue, UCSD Ped1, and UCSD Peds2. The experimental results have shown that the proposed framework models the complex distribution of the pattern of regular motion changes with high accuracy. Besides, this method was observed to outperform state-of-the-art approaches based on unsupervised and semi-supervised deep learning models.

Detection of Moving Objects by a Passive Scanning System

The problem of detection and estimation of spatial coordinates of moving objects by a passive scanning system of vision is solved. Algebraic and algorithmic approaches to determining the spatial coordinates and parameters of object motion are proposed. These approaches differ by taking into account the object velocities in searching for conjugate vectors of directions to the objects. The algorithms developed on the basis of these approaches show that the approach with allowance for motion parameters offers significant advantages of higher accuracy of coordinate estimation and higher probability of detecting all objects.

Robust Precision Manipulation With Simple Process Models Using Visual Servoing Techniques With Disturbance Rejection

This paper presents a high-performance vision-based precision manipulation technique that does not rely on an object, contact, or gripper model, which are challenging and often times impractical to acquire. Instead, we utilize a simple process model that roughly maps object velocities to actuator velocities, and we maintain system efficiency and robustness via advanced vision-based control techniques with disturbance rejection mechanisms. For obtaining simple models, we derive a set of actuator coordination rules for achieving common task space motions. The performance degradation due to modeling inaccuracies is then minimized via the model predictive control framework and a correction matrix method. Our experimental results show that the proposed strategy results in high-performance precision manipulation with minimal modeling effort. Note to Practitioners —Compliant, soft robotic grippers make it easier to grasp objects with various shapes and sizes; these grippers adapt to the shape of the object, which provides robustness to positioning errors and often removes the necessity to precisely plan the contact locations. These advantages make compliant grippers ideal to use in industrial settings as well as in service robotics, where the variety of object shapes and sizes are immense. On the other hand, for the tasks that require precise object manipulation (e.g., for a peg-in-hole problem), these hands are more challenging to control than their rigid counterparts: it is harder to obtain their precise models, and they often do not have enough proprioceptive sensors to calculate the full pose of the system. In this paper, we propose solutions to utilize vision feedback for positioning an object using compliant hands. These solutions do not rely on precise models of the gripper or the full knowledge of the gripper state. We adopt various control techniques to provide precise positioning in steady state as well as to maintain efficiency in the transient.

Detection and Measurement of Displacement and Velocity of Single Moving Object in a Stationary Background

The traditional Harris detector are sensitive to noise and resolution because without the property of scale invariant. In this research, The Harris corner detector algorithm is improved, to work with multi resolution images, the technique has also been working with poor lighting condition by using histogram equalization technique. The work we have done addresses the issue of robustly detection of feature points, detected multiple of local features are characterized by the intensity changes in both horizontal and vertical direction which is called corner features. The goal of this work is to detect the corner of an object through the Harris corner detector with multiple scale of the same image. The scale invariant property applied to the Harris algorithm for improving the corner detection performance in different resolution of the same image with the same interest point. The detected points represented by two independent variables (x, y) in a matrix (x, y) and the dependent variable f are called intensity of interest points. Through these independent variable, we get the displacement and velocity of object by subtracting independent variable f(x,y) at current frame from the previous location f ̀((x,) ̀(y,) ̀) of another frame. For further work, multiple of moving object environment have been taken consideration for developing algorithms.

5 Detection and Measurement of Displacement and Velocity of Single Moving Object in a Stationary Background

The traditional Harris detector are sensitive to noise and resolution because without the property of scale invariant. In this research, The Harris corner detector algorithm is improved, to work with multi resolution images, the technique has also been working with poor lighting condition by using histogram equalization technique. The work we have done addresses the issue of robustly detection of feature points, detected multiple of local features are characterized by the intensity changes in both horizontal and vertical direction which is called corner features. The goal of this work is to detect the corner of an object through the Harris corner detector with multiple scale of the same image. The scale invariant property applied to the Harris algorithm for improving the corner detection performance in different resolution of the same image with the same interest point. The detected points represented by two independent variables (x, y) in a matrix (x, y) and the dependent variable f are called intensity of interest points. Through these independent variable, we get the displacement and velocity of object by subtracting independent variable f(x,y) at current frame from the previous location f ̀((x,) ̀(y,) ̀) of another frame. For further work, multiple of moving object environment have been taken consideration for developing algorithms.

Detection and Measurement of Displacement and Velocity of Single Moving Object in a Stationary Background

The traditional Harris detector are sensitive to noise and resolution because without the property of scale invariant. In this research, The Harris corner detector algorithm is improved, to work with multi resolution images, the technique has also been working with poor lighting condition by using histogram equalization technique. The work we have done addresses the issue of robustly detection of feature points, detected multiple of local features are characterized by the intensity changes in both horizontal and vertical direction which is called corner features. The goal of this work is to detect the corner of an object through the Harris corner detector with multiple scale of the same image. The scale invariant property applied to the Harris algorithm for improving the corner detection performance in different resolution of the same image with the same interest point. The detected points represented by two independent variables (x, y) in a matrix (x, y) and the dependent variable f are called intensity of interest points. Through these independent variable, we get the displacement and velocity of object by subtracting independent variable f(x,y) at current frame from the previous location f ̀((x,) ̀(y,) ̀) of another frame. For further work, multiple of moving object environment have been taken consideration for developing algorithms.

Observability and sensitivity analysis of lightcurve measurement models for use in space situational awareness

ABSTRACTThis paper deals with the observability and sensitivity analysis of the lightcurve measurement for use in the estimation of instantaneous pose (orientation) and shape geometry. Since several reflectance models exist that are typically used in obtaining a synthetic lightcurve measurement, they are compared to assess the observability or/and ‘sensitivity’ to determine the ‘best model’ for use. These measurement models are nonlinear with implicit and non-trivial dependency on the states; a numerical Jacobian as well as an unscented Kalman filter derived observation matrix are synthesized for each choice of the measurement model and compared. As the linearization is about an attitude (orientation) trajectory, distinct cases are considered to elaborate the results. For the cases evaluated here, it is shown that the attitude and shape/size can indeed be estimated from the lightcurve, but this is also dependent upon the initial conditions (subsequent attitude trajectory). Linear observability analysis of a discretized system is also performed with respect to the attitude states and shape/size parameters using the singular value decomposition of the observability matrix synthesized for a batch of measurements. The results are summarized for various initial conditions of the resident space object's attitude and angular velocity states.

A Pure Mathematical Argument for Finiteness of Velocity of Material Objects

Purely by mathematical means a theorem of the finiteness of the velocity of material objects is proved without reference to the special theory of relativity. The Proof is valid under the condition that in material objects there are always present interaction signals (carrier particles) without rest mass that are propagated at a velocity greater than any achieved velocity of the particles and bodies with rest mass, moreover, the interaction signals (carrier particles) colliding with elements of these objects continuously initiate interactions and processes in all objects. The condition does not in itself contain any limitation of the velocity of material objects. Neither does it contradict it. The arguments presented in this paper can be tied to any inertial reference system by virtue of the formal equality of these systems.