Non-straight Paths Research Articles

A computational method for calculating the electrical and thermal conductivity of random composites

In the present work, for the first time, the electrical–thermal conductivity of a composite random material is correlated with the number of conductive paths, the mean path length, and the mean effective path width measured in a representative surface element (RSE) by Monte Carlo sampling. This work is organized in two parts. The theoretical calculation takes place in the first part for the correlation of conductive paths by adopting three approaches (incremental with respect to accuracy and complexity) based on: (i) one-component straight paths; (ii) one-component non-straight paths; (iii) multi-component non-straight paths. In the second part, a novel numerical methodology for the calculation of the conductance of the RSE through the conductive paths, mean path length and the mean effective path is developed for the general model of multi-component non-straight line paths based on Ohm’s law. In addition, a methodology that reduces the calculated conductivity from the microscale to the macroscale is proposed, that takes into account the probability of percolation for finite sizes and the average value of the conductivity from the samples in which percolation occurs. After the necessary consistency steps and verification of the method and its implementation on random binary material systems, it is further applied to solve synthetic continuous percolation problems at the microscale and macroscale. The results and the accuracy of the calculations are in close agreement with existing models. The electrical Direct Current (DC) and thermal conductivity follow the same scaling relation and the proposed methodology can be applied at the same stage without additional cost. In a random binary medium the simulations showed that a scaling law of conductivity is followed by an exponent value close to 1.3. In addition, the number of conductive paths, the average length of the paths, and the effective width follow scaling laws with exponents 1.44±0.01 , −0.25±0.01 and −0.39±0.01, respectively.

Generalizing stepping concepts to non-straight walking

People rarely walk in straight lines. Instead, we make frequent turns or other maneuvers. Spatiotemporal parameters fundamentally characterize gait. For straight walking, these parameters are well-defined for the task of walking on a straight path. Generalizing these concepts to non-straight walking, however, is not straightforward. People follow non-straight paths imposed by their environment (sidewalk, windy hiking trail, etc.) or choose readily-predictable, stereotypical paths of their own. People actively maintain lateral position to stay on their path and readily adapt their stepping when their path changes. We therefore propose a conceptually coherent convention that defines step lengths and widths relative to predefined walking paths. Our convention simply re-aligns lab-based coordinates to be tangent to a walker’s path at the mid-point between the two footsteps that define each step. We hypothesized this would yield results both more correct and more consistent with notions from straight walking. We defined several common non-straight walking tasks: single turns, lateral lane changes, walking on circular paths, and walking on arbitrary curvilinear paths. For each, we simulated idealized step sequences denoting “perfect” performance with known constant step lengths and widths. We compared results to path-independent alternatives. For each, we directly quantified accuracy relative to known true values. Results strongly confirmed our hypothesis. Our convention returned vastly smaller errors and introduced no artificial stepping asymmetries across all tasks. All results for our convention rationally generalized concepts from straight walking. Taking walking paths explicitly into account as important task goals themselves thus resolves conceptual ambiguities of prior approaches.

Survival on land: A dark-grown seedling searching for path.

To initiate its development into a plant, a small dark-grown seedling (prior to its emergence from the ground) must penetrate through the growth media. The path that the seedling takes during this journey has yet to be explained. As such, we conducted non-destructive tests using CT scans to observe the growth of dark-grown seedlings in soil over time; we also developed a model to simulate the dynamics of an emerging seedling, and to examine effects of various growth medium conditions, including Lunar soil. It was previously postulated that, with gravitropism in a terrestrial growth medium, a dark-grown seedling would grow directly upright. However, our CT scan results showed that dark-grown soybean seedlings departed from the vertical path in soil, as far as a lateral distance of approximately 10mm. The phenomenon of the non-straight path was also demonstrated by the model results. Through simulations, we found that an emerging seedling naturally weaves through the particles of growth medium, in search for the path of least resistance. As a result, the seedling ends up travelling a longer distance. Compared with a seedling that was artificially forced to take a straight path in a growth media, the seedling taking the natural path encountered significantly lower resistances (20% lower) from the growth medium, while travelled 12% longer distance during the emergence process. A seedling encountered a much higher impedance in Lunar soil. Our results suggest that taking the path of least resistance, in addition to shaping and orientating itself for mechanical advantage, are strategies evolved by plant species that have contributed to its vast success. An understanding of plant behavior and survival strategies on Earth lay the foundation for future research in agriculture in novel environments, including on celestial bodies.

An enhanced RSS-distance-angle weighted geometric filter for device-free localization

Device-free localization and tracking as an emerging technology has attracted substantial research attention in wireless sensor networks. However, there is much room for improvement in localization and tracking accuracy. In this paper, by using received signal strength (RSS) measurements we propose an enhanced geometric filter which consists of a series of weights corresponding to RSS, distance, and angle, respectively. Specifically, RSS-based weights are dependent on the change in RSS of communication links to remove improbable target locations. To ensure robust tracking performance, distance-based weights are assigned to probable target locations. Angle-based weights are used to ensure the correct direction of motion. Experimental results demonstrate that the proposed geometric filter could improve the accuracy of positioning by up to 50.8% for non-straight path and 48.3% for straight path over some state-of-the-art methods.

Three-dimensional dynamics of a pair of deformable bubbles rising initially in line. Part 2. Highly inertial regimes

The buoyancy-driven dynamics of a pair of gas bubbles released in line is investigated numerically, focusing on highly inertial conditions under which isolated bubbles follow non-straight paths. In an early stage, the second bubble always drifts out of the wake of the leading one. Then, depending on the ratios of the buoyancy, viscous and capillary forces which define the Galilei ( $Ga$ ) and Bond ( $Bo$ ) numbers of the system, five distinct regimes specific to such conditions are identified, in which the two bubbles may rise independently or continue to interact and possibly collide in the end. In the former case, they usually perform large-amplitude planar zigzags within the same plane or within two distinct planes, depending on the oblateness of the leading bubble. However, for large enough $Ga$ and low enough $Bo$ , they follow nearly vertical paths with small-amplitude erratic horizontal deviations. Increasing $Bo$ makes the wake-induced attraction toward the leading bubble stronger, forcing the two bubbles to realign vertically one or more times along their ascent. During such sequences, wake vortices may hit the trailing bubble, deflecting its path and, depending on the case, promoting or hindering further possibilities of interaction. In some regimes, varying the initial distance separating the two bubbles modifies their lateral separation beyond the initial stage. Similarly, minute initial angular deviations favour the selection of a single vertical plane of rise common to both bubbles. These changes may dramatically affect the fate of the tandem as, depending on $Bo$ , they promote or prevent future vertical realignments.

Real-Time, Robot-Based, 3D Localization of RFID Tags, by Transforming Phase Measurements to a Linear Optimization Problem

In this paper, we propose a prototype method for fast and accurate 3D localization of RFID-tagged items by a mobile robot. The robot performs Simultaneous Localization of its own pose and Mapping of the surrounding environment (SLAM). It is equipped with RFID readers and antennas placed at different heights, collecting phase-measurements by all tags. Thanks to the self-localization property of the robot, a synthetic aperture is created for each tag. In this paper, we have manipulated the set of phase-measurements, combined with the known poses of the robot to craft an overdetermined system of linear equations which pinpoints the location of the tag. The linearity of the system preserves that localization is achieved rapidly. The problem is solved for any arbitrary movement of the robot and extended in three dimensions. The proposed method is experimentally compared against the state-of-the-art in SAR-based RFID localization. It is the fastest and the most accurate, when the robot moves along straight-paths. Its accuracy slightly worsens, when the robot moves along non-straight paths, while preserving its exceptionally small running-time. It can be applied in real-time 3D localization problems, demonstrating mean 3D accuracy below 20 cm.

Calculating 1/β2p2 for most likely path estimates for protons and helium ions using an analytical model.

In ion computed tomography, limited spatial resolution can be related to the non-straight path of ions resulting from multiple Coulomb scattering in the object to be imaged. By including sophisticated path estimates such as most likely path (MLP) or optimized cubic spline into the image reconstruction algorithm, the achieved spatial resolution can be substantially improved compared to assuming a simple straight line path only. The typically used implementation of the MLP is a matrix-based approach employing Bayesian statistics and modelling multiple Coulomb scattering as Gaussian distribution. For the elements of the scattering matrices, the term 1/β(w)2p(w)2, depending on the momentum and velocity of an ion within a phantom depth w, has to be known and integrated along the depth w. Usually, this term is extracted from a Monte Carlo simulation and approximated by a polynomial fit to solve the integral. In the present study, an existing analytical model for ion ranges and stopping powers was used to calculate 1/β(w)2p(w)2 and the scattering matrices for the MLP and was tested for protons and helium ions. The model was investigated for 10cm to 40cm water targets and initial energies ranging from 150MeV to 300MeV for protons and 150MeV/u to 300MeV/u for helium ions. In all cases, the calculated value obtained for 1/β(w)2p(w)2 was compared to a GATE simulation. The difference between root-mean-square errors of MLP estimates using calculated and simulated 1/β(w)2p(w)2 values were found to be smaller than 3μm for all investigated water targets and energies.

Optimization of Longitudinal Control of an Autonomous Vehicle using Flower Pollination Algorithm based on Data-driven Approach

Some challenges in the development of autonomous vehicles, such as generating a model representing the dynamics of the speed, designing a longitudinal controller, and the optimization method, are still explored until now. In this paper, a longitudinal controller based on the proportional-integral-derivative controller with an additional feed- forward term is proposed, where the Flower Pollination Algorithm is employed for optimizing the controller. The feed-forward term and the model used in the optimization are generated using the data-driven approach. For the optimization, a cost function considering mean absolute error and mean absolute jerk will be minimized. The simulation study was performed using the CARLA simulator, and the results show that the proposed scheme represents the dynamics of the speed very well inside the range of the training data and does not overfit the training data. It is also demonstrated that the proposed longitudinal controller can track the desired speed satisfactorily in a non-straight path.

Range and Bearing Estimation of an UHF-RFID Tag Using the Phase of the Backscattered Signal

The narrow bandwidth of UHF RFID signals does not allow the direct measurement of the range between the reader and the tag. A Multi-Hypothesis Extended Kalman Filter is proposed in this paper to solve this issue, by fusing the phase measurements with the odometry readings of a mobile robot. While estimating the tag-reader distance, the proposed approach provides also an on-line estimation of the bearing of the tag. The knowledge of range and bearing is beneficial in positioning-based applications as in robotics, to develop algorithms for reaching and grasping a tagged object or to localize a robot using tags as anchors, or for solving a Simultaneous Localization and Mapping (SLAM) problem if positions of both tags and robot are unknown. A few steps are usually enough to obtain a univocal effective estimate of these quantities, as long as the robot is moving over a non-straight path. A comprehensive numerical analysis supports and assesses the theory.

Motor atypicalities in infancy are associated with general developmental level at 2 years, but not autistic symptoms.

Atypical motor development has frequently been reported in infants at elevated likelihood for autism spectrum disorder. However, no previous study has used detailed motion capture technology to compare infant siblings of children with autism spectrum disorder and infant siblings with no familial history of autism spectrum disorder. We investigated reaching movements during an interceptive action task in 10-month-old infants using kinematic data with high spatiotemporal resolution. The results indicated that several measures were different in infants at elevated likelihood. However, longitudinal analyses revealed that while specific infant motor measures (e.g. number of movement units) were related to broad measures of general developmental level in toddlerhood, the associations with later autism spectrum disorder symptomatology were not significant. These findings confirm that some aspects of motor functioning are atypical in infants at elevated likelihood for autism spectrum disorder, but provide no support for the view that these issues are specifically linked to autism spectrum disorder symptoms, but may rather reflect neurodevelopment more generally.Lay abstractAtypicalities in motor functioning are often observed in later born infant siblings of children with autism spectrum disorder. The goal of our study was to investigate motor functioning in infants with and without familial history of autism spectrum disorder. Specifically, we investigated how infants catch a ball that is rolling toward them following a non-straight path, a task that requires both efficient planning and execution. Their performance was measured using detailed three-dimensional motion capture technology. We found that several early motor functioning measures were different in infants with an older autistic sibling compared to controls. However, these early motor measures were not related to autistic symptoms at the age of 2 years. Instead, we found that some of the early motor measures were related to their subsequent non-social, general development. The findings of our study help us understand motor functioning early in life and how motor functioning is related to other aspects of development.

Review of the Book Predicting Vehicle Trajectory [Book Review

The book concentrates on the improvement of the prediction of a future vehicle trajectory, giving emphasis on the cases of non-straight paths. The trajectory is the path that a moving object (in our case a vehicle) follows through space as a function of time. In several cases in our physical world, trajectories can be described mathematically either by the geometry of the path or as the position of the object over time. However, in intelligent transportation systems this is not applicable and therefore having a reliable prediction of a vehicle position in the very near future is crucial to determine possible path intersections, collisions of vehicles or diversion from the road. As stated in the book “The US Department of Transportation will be mandating that all vehicle manufacturers begin implementing Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) systems, so very soon collision avoidance systems will no longer rely on line of sight sensors, but instead will be able to take into account another vehicle’s spatial movements to determine if the future trajectories of the vehicles will intersect at the same time”. To this end, this book offers the reader some improvements for predicting the future trajectory of a vehicle and presents a novel temporary solution on how to speed up the implementation of such V2V collision avoidance systems. Additionally, the book evaluates whether smartphones can be used for trajectory predictions, to populate a V2V collision avoidance system faster than a vehicle manufacturer can.

Intelligent Forecasting Using Dead Reckoning With Dynamic Errors

A method for integrating, processing, and analyzing sensing data from vehicle-mounted sensors for intelligent forecasting and decision-making is introduced. This dead reckoning with dynamic errors (DRWDEs) is for a large-scale integration of distributed resources and sensing data intervehicle collision avoidance system. This sensor fusion algorithm is introduced to predict the future trajectory of a vehicle. Current systems that predict a vehicle's future trajectory, necessary in a network of collision avoidance systems, tend to have a lot of errors when the vehicles are moving in a nonstraight path. Our system has been designed with the objective of improving the estimations during curves. To evaluate this system, our research uses a Garmin 16HVS GPS sensor, an AutoEnginuity OBDII ScanTool, and a Crossbow three-axis accelerometer. Using Kalman filters (KFs), a dynamic noise covariance matrix merged together with an interacting multiple models (IMMs) system, our DRWDE produces the future position estimation of where the vehicle will be 3 s later in time. The ability to handle the change in noise, depending on unavailable sensor measurements, permits a flexibility to use any type of sensor and still have the system run at the fastest frequency available. Compared with a more common KF implementation that runs at the rate of its slowest sensor (1 Hz in our setup), our experimental results showed that our DRWDE (running at 10 Hz) yielded more accurate predictions (25%-50% improvement) during abrupt changes in the heading of the vehicle.

PACDIN statement of methods

PAntograph–Catenary Dynamic Interaction (PACDIN) is a code developed by the vehicle technology research centre (CITV) of the Universitat Politècnica de València in collaboration with the railway company Talgo S.L. The model of the catenary is a finite element model using absolute nodal coordinates. It is based on a general formulation that can be applied for analysing a wide range of catenary configurations, including stitch wire, transitions or non-straight path tracks. The formulation is fully non-linear and includes large deformations, dropper slackening and contact interaction. The model is linearised when deformations are small, as in the case of the benchmark dynamic analysis. The results of the PACDIN code show a good agreement with the average results of other benchmark codes.

Non-Almost Periodicity of Parallel Transports for Homogeneous Connections

Let \({\cal A}\) be the affine space of all connections in an SU(2) principal fibre bundle over ℝ3. The set of homogeneous isotropic connections forms a line l in \({\cal A}\). We prove that the parallel transports for general, non-straight paths in the base manifold do not depend almost periodically on l. Consequently, the embedding \(l \hookrightarrow {\cal A}\) does not continuously extend to an embedding \(\overline{l} \hookrightarrow \overline{\cal A}\) of the respective compactifications. Here, the Bohr compactification \(\overline{l}\) corresponds to the configuration space of homogeneous isotropic loop quantum cosmology and \(\overline{\cal A}\) to that of loop quantum gravity. Analogous results are given for the anisotropic case.

Wake-Induced Oscillatory Paths of Bodies Freely Rising or Falling in Fluids

Leaves falling in air and bubbles rising in water provide daily examples of nonstraight paths associated with the buoyancy-driven motion of a body in a fluid. Such paths are relevant to a large variety of applicative fields such as mechanical engineering, aerodynamics, meteorology, and the biomechanics of plants and insect flight. Although the problem has attracted attention for ages, it is only recently that the tremendous progress in the development of experimental and computational techniques and the emergence of new theoretical concepts have led to a better understanding of the underlying physical mechanisms. This review attempts to bring together the main recent experimental, computational, and theoretical advances obtained on this fascinating subject. To this end it describes the first steps of the transition in the wake of a fixed body and its connection with the onset and development of the path instability of moving bodies. Then it analyzes the kinematics and dynamics of various types of bodies along typical nonstraight paths and how the corresponding information can be used to build low-dimensional predictive models.

Experimental validation of the constitutive equations of thermoelastoplasticity including the third invariant of the stress deviator

The equations describing thermoelastoplastic deformation along nonstraight paths and taking into account the third invariant of the stress deviator are experimentally validated. The equations contain two scalar functions that are specified in base tests on tubular specimens. The test data are tabulated. The values of the scalar functions for strains, temperature, and stress mode are found by using nonlinear interpolation of the data and the temperature similarity of the functions. The stresses in elements of the body are calculated from given strains by the method of successive approximations

Reactive Path Planning for 3-D Autonomous Vehicles

This brief deals with the problem of path planning for 3-D vehicles. The problem is simplified by resolving the workspace into horizontal and vertical planes. The flight path angle and the heading angle are linear functions of the visibility line angles in the vertical and horizontal planes, respectively. Other terms for the deviation and heading regulation are added to the navigation law. The navigation law has two navigation proportionality factors and two deviation parameters corresponding to the horizontal and vertical planes. The method has the ability to generate non-straight paths to the goal. Obstacles and dangerous zones are avoided by correcting the path by changing the values of the parameters. The dynamic constraints are transformed to a restriction in the navigation parameters' space. Our results are illustrated using simulation.

Reducing a class of polygonal path tracking to straight line tracking via nonlinear strip-wise affine transformation

In this paper a piecewise linear homeomorphism is presented that maps a strictly monotone polygonal chain to a straight line. This mapping enables one to reduce the path tracking task for mobile robots to straight line tracking. Due to the simplicity of the transformation, closed form solutions for the direct and inverse mapping are presented. Furthermore, the transformation also defines a feedback equivalence relation between the original and the transformed system equations of the mobile robot. It is shown that the form of the system equations is preserved and that the transformation essentially maps a car-like robot in the original domain, to a car-like robot in the transformed domain. This enables one to use straight line trackers developed solely for this system, for the tracking of arbitrary strictly monotone polygonal curves. Finally, it is shown that the use of this mapping can also simplify the application of existing path tracking controllers since they only need to track straight line paths. In general, one can eliminate from the existing path controllers all parameters that are needed for non-straight paths, thus obtaining respective simplified controllers. For example, it is shown that a fuzzy path controller with 135 rules can be reduced to an equivalent fuzzy straight line tracking controller with 45 rules.

Non-interferometric methods of phase estimation for application in optical tomography

Abstract We describe here two non-interferometric methods for the estimation of the phase of transmitted wavefronts through refracting objects. The phase of the wavefronts obtained is used to reconstruct either the refractive index distribution of the objects or their contours. Refraction corrected reconstructions are obtained by the application of an iterative loop incorporating digital ray tracing for forward propagation and a modified filtered back projection (FBP) for reconstruction. The FBP is modified to take into account non-straight path propagation of light through the object. When the iteration stagnates, the difference between the projection data and an estimate of it obtained by ray tracing through the final reconstruction is reconstructed using a diffraction tomography algorithm. The reconstruction so obtained, viewed as a correction term, is added to the estimate of the object from the loop to obtain an improved final refractive index reconstruction.

Non-interferometric methods of phase estimation for application in optical tomography

We describe here two non-interferometric methods for the estimation of the phase of transmitted wavefronts through refracting objects. The phase of the wavefronts obtained is used to reconstruct either the refractive index distribution of the objects or their contours. Refraction corrected reconstructions are obtained by the application of an iterative loop incorporating digital ray tracing for forward propagation and a modified filtered back projection (FBP) for reconstruction. The FBP is modified to take into account non-straight path propagation of light through the object. When the iteration stagnates, the difference between the projection data and an estimate of it obtained by ray tracing through the final reconstruction is reconstructed using a diffraction tomography algorithm. The reconstruction so obtained, viewed as a correction term, is added to the estimate of the object from the loop to obtain an improved final refractive index reconstruction.