Trajectory Path Research Articles

On the use of edge cracked short bend beam specimen for PMMA fracture toughness testing under mixed-mode I/II

In this paper an inclined edge cracked short beam specimen subjected to symmetric three-point bend loading was designed and examined for conducting mixed-mode I/II fracture toughness experiments. The aspect ratio (i.e. length to width ratio) and the loading span distance are considered much lower than the other conventional cracked bend beam samples. Crack tip parameters such as stress intensity factors and T-stress were computed numerically for this specimen by several finite element analyses and it was demonstrated that the specimen is able to produce full combinations of mode I and II including pure mode II. The practical capability of the short bend beam specimen was studied experimentally by conducting a set of mixed-mode fracture tests on PolymethylMethacrylate (PMMA) as a well-known model brittle material. The critical stress intensity factors, the direction of fracture kinking and the path of fracture trajectory were investigated both experimentally and theoretically using two stress and strain-based fracture criteria. The fracture toughness of tested PMMA was decreased by moving towards mode II case due to the effect of T-stress on the fracture mechanism of the short bend beam specimen.

Real-Time Autonomous Spacecraft Proximity Maneuvers and Docking Using an Adaptive Artificial Potential Field Approach

In an effort to pursue more advanced missions in space, improved on-board trajectory optimization and path (re)planning capabilities are necessary. Over the past decades, numerous missions have pushed the state of the art in autonomous rendezvous and proximity operations (RPOs). Regardless of the mission, any RPO guidance algorithm must be able to react to a dynamic environment while generating a fuel-efficient trajectory. An adaptive artificial potential function (AAPF) guidance exhibiting these properties has been experimentally evaluated on a spacecraft air-bearing test bed and its performance compared to traditional APF and other real-time guidance methods.

Early event understanding predicts later verb comprehension and motion event lexicalization.

Before infants produce words, they can discriminate changes in motion event components such as manner (how an action is performed) and path (trajectory of an action). Individual differences in nonlinguistic event categorization are related to children's later verb comprehension (Konishi, Stahl, Golinkoff, & Hirsh-Pasek, 2016). We asked: (a) Do infants learning Turkish, a verb-framed language, attend to both manner and path changes in motion events? (b) Is early detection of path and manner related to children's later verb comprehension and (c) how they describe motion events? Thirty-two Turkish-reared children were tested at three time points. At Time 1, infants (Mage = 14.5months) were tested on their detection of changes in path and manner using the Preferential Looking Paradigm. At Time 2, children were tested on their receptive language skills (Mage = 22.07months). At Time 3, children performed 3 tasks (Mage = 35.05months): a verb comprehension task, an event description task depicting motion events with different path and manner combinations, and an expressive language task. The ability to detect changes in event components at Time 1 predicted verb comprehension abilities at Time 3, beyond general receptive and expressive vocabulary skills at Times 2 and 3. Infants who noticed changes in path and manner at Time 1 used fewer manner-only descriptions and more path-any descriptions (i.e., descriptions that included a path component with or without manner) in their speech at Time 3. These findings suggest that early detection of event components is associated not only with verb comprehension, but also with how children lexicalize event components in line with their native language. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Development of GPS-based Tracking System to Evaluate the Effectiveness of Tillage using Four-wheel Tractor

The objective of this study was to present the development of GPS-based tracking system to evaluate the effectiveness of tillage using a four-wheel tractor. The system is composed of a location acquisition, using GPS (iGPSport), and data analysis for estimating the tractor trajectories and effectiveness of tillage by measuring the overlap during the tillage. The laboratory stage experiment was conducted to validate the system by measuring the specified size of the field and tractor trajectories. The performance evaluation of the system was done by measuring the displacement error of actual trajectories and the estimated one. The system was also tested for the actual tillage operation using a four-wheel tractor, Daedong Kioti RX7210, in two locations in Yogyakarta: Pajangan, and Moyudan. The tractor tracking system was developed based on GPS for estimating the tractor trajectory path and operation width distance (l) after the operation as tillage effectiveness evaluation by the evaluation of overlap and untillage land systematically using the tracking system. The system performance evaluation in the actual field for tillage operation using the four-wheel tractor in Moyudan and Pajangan shows that the RMSE < 50 cm, and the MAPE < 24% with R2 > 0.7. Overall performance of the tracking system, it could be used to estimate the behavior of tillage operation.

Analytical and experimental investigations on the mechanisms of surface generation in micro grinding

Micro grinding is an emerging technology for producing structured surfaces on hard and brittle materials. A micro pencil grinding tool (MPGT) consists of a layer of superabrasive grits, bonded to a solid cylindrical surface. Randomly distributed and geometrically undefined grits interact with the workpiece surface at random positions. These random grit positions and protrusions lead to a difference in the size of undeformed chips. This study presents an analytical method to understand the undeformed chip geometry, that considers grit kinematics. Kinematic simulation of grit trajectory paths in longitudinal direction showed a reduced number of active grits in micro grinding with an increase in speed ratio and with reduced tool dimensions. MPGTs with different diameters, grit sizes, and planar grit densities have been used to perform the experiments on a 16MnCr5 hardened steel material. The influence of maximum radial height grits on surface generation in micro grinding has been verified experimentally for up and down grinding modes. Microscopic observations of ground surfaces have shown the distinct differences between up and down grinding modes, which are similar to the surface generation in milling processes. Moreover, the formation of linear grooves with uniform depth and width unlike conventional surface grinding at lower speed ratios indicated the influence of individual grits on surface generation. Trajectory path simulation results have also shown the same observation.

Roadkill and space use data predict vehicle-strike hotspots and mortality rates in a recovering bobcat (Lynx rufus) population

Roadways pose challenges for conserving wide-ranging animal species. As bobcat (Lynx rufus) populations recover in Ohio, an accurate evaluation of population metrics is critical to understanding future population trajectories. In this study, we integrated multiple datasets to examine overall road mortality rates in Ohio. First, we utilized a long-term vehicle-strike dataset (1978–2017) to determine landscape and local predictors of road mortality. We found that bobcats were killed at higher rates on interstates regardless of surrounding landscape composition, but that landscape variables were useful at predicting mortality on lower-traffic roads. To explore road avoidance behaviors, we used GPS telemetry data from 18 individuals to compare road crossings along trajectory paths with random road crossings simulated using Correlated Random Walks. Bobcats exhibited avoidance of certain route types (county, municipal, and US routes). Finally, by integrating traffic volume data, road crossing behavior, and accounting for the proportion of each route type present in the study area, we estimated that a minimum of 6% and up to 18% of the bobcat population in Ohio is lost to vehicle-strikes annually. To fully understand the population level impacts of this mortality, we recommend further monitoring of age structure and sex of roadkill animals. Our results identify potential areas for mitigation of vehicle-strikes and emphasize the importance of accounting for road mortality when making management decisions for Ohio’s recovering bobcat population.

Trail optimization framework to detect nonlinear object motion in video sequences

Detecting and tracking multiple moving objects in a sequence of video images is an important application in automated surveillance systems, service robots, target discrimination, traffic monitoring, etc. Since these systems require real-time processing, providing an efficient method with lower computational complexity is a challenge. Besides the combination of rudimentary techniques which works well for linear objects, this paper presents an operative technique to recognize and track multiobject moving in a video sequence without using additional trackers. Instead of processing the entire video sequence, candidate keyframes are identified and the foreground moving objects are detected. To solve the nonlinear tracking problem, this paper presents an optimized twin algorithm—amended Kalman with Hungarian algorithm—to track multiple moving objects on their center of gravity in the minimal bounding box. Kalman filter predicts the location of the foreground objects in various orientation bins to extract the short-term movement of the foreground objects in possible trajectory paths. Hungarian algorithm locates the presence/absence of nonlinear objects in the tracks. Location prediction and tracking of moving objects only on the candidate frames reduces the computation time. Therefore, it is a good alternative method for nonlinear motion estimation that is likely required for multiobject identity tracking in image sequences. This approach achieves high accuracy and reduces additional computations comparable to state-of-the-art online trackers. The comparison also proved that the proposed method has better precision–recall values with computation simplicity.

Treatment planning optimization with beam motion modeling for dynamic arc delivery of SBRT using Cyberknife with multileaf collimation.

PurposeThe use of dynamic arcs for delivery of stereotactic body radiation therapy (SBRT) on Cyberknife is investigated, with a view to improving treatment times. This study investigates the required modeling of robot and multileaf collimator (MLC) motion between control points in the trajectory and then uses this to develop an optimization method for treatment planning of a dynamic arc with Cyberknife. The resulting plans are compared in terms of dose‐volume histograms and estimated treatment times with those produced by a conventional beam arrangement.MethodsFive SBRT patient cases (prostate A — conventional, prostate B — brachytherapy‐type, lung, liver, and partial left breast) were retrospectively studied. A suitable arc trajectory with control points spaced at 5° was proposed and treatment plans were produced for typical clinical protocols. The optimization consisted of a fluence optimization, segmentation, and direct aperture optimization using a gradient descent method. Dose delivered by the moving MLC was either taken to be the dose delivered discretely at the control points or modeled using effective fluence delivered between control points. The accuracy of calculated dose was assessed by recalculating after optimization using five interpolated beams and 100 interpolated apertures between each optimization control point. The resulting plans were compared using dose‐volume histograms and estimated treatment times with those for a conventional Cyberknife beam arrangement.ResultsIf optimization is performed based on discrete doses delivered at the arc control points, large differences of up to 40% of the prescribed dose are seen when recalculating with interpolation. When the effective fluence between control points is taken into account during optimization, dosimetric differences are <2% for most structures when the plans are recalculated using intermediate nodes, but there are differences of up to 15% peripherally. Treatment plan quality is comparable between the arc trajectory and conventional body path. All plans meet the relevant clinical goals, with the exception of specific structures which overlap with the planning target volume. Median estimated treatment time is 355 s (range 235–672 s) for arc delivery and 675 s (range 554–1025 s) for conventional delivery.ConclusionsThe method of using effective fluence to model MLC motion between control points is sufficiently accurate to provide for accurate inverse planning of dynamic arcs with Cyberknife. The proposed arcing method produces treatment plans with comparable quality to the body path, with reduced estimated treatment delivery time.

Optimal trajectory planning of industrial robot for improving positional accuracy

Purpose The purpose of this paper is to improve the positional accuracy, smoothness on motion and productivity of industrial robot through the proposed optimal joint trajectory planning method. Also a new improved algorithm, i.e. non-dominated sorting genetic algorithm-II (NSGA-II) with achievement scalarizing function (ASF) has been proposed to obtain better optimal results compared to previously used optimization methods. Design/methodology/approach The end effector positional errors can be reduced by limiting the uncertainties of dynamic parameter variations like torque rate of joints. The jerk induced in robot joints due to acceleration variations are need to be minimized which otherwise induces vibrations in the manipulator that causes deviation in the encoders. But these lead to a vast increase in total travel time which affects the cost function of trajectory planning. Therefore, these three objectives need to be minimized individually so that an optimal trajectory path can be achieved with minimum positional error. Findings The simulation results have been obtained by running the proposed hybrid NSGA-II with ASF in MATLAB R2017a software. The optimal time intervals have been used to calculate jerk, acceleration and torque values for consecutive points on the trajectory path. From the simulation and experimental results, it can be concluded that the optimization technique could be used effectively for the trajectory planning of six-axis industrial manipulator in the joint space on the basis of minimum time-jerk-torque rate criteria. Originality/value In this paper, a new approach based on hybrid multi-objective optimization technique by combining NSGA-II with ASF has been applied to find the minimal time-jerk- torque rate joint trajectory of a six-axis industrial robot for obtaining higher positional accuracy. The results obtained from the execution of algorithm have been validated through experimentation using Kawasaki RS06L industrial robot for a particular defined path.

Improving traffic network performance with road banning strategy: A simulation approach comparing user equilibrium and system optimum

The purpose of this study is to compare network loadings related to different network equilibria by a simulation-based framework. The direct comparison of path flows or trajectory patterns is hard to achieve so here we propose a more aggregate approach based on the comparison of demand level breakpoints. A breakpoint is a demand threshold value that leads to significant changes in path flow loading. More specifically, we set in this paper a demand breakpoint when the list of effective route alternatives differs by at least one path. This is for example the case when one route is no longer considered for one equilibrium while being used by some vehicles in the second one. We are going to investigate both static and dynamic network loading while scanning all demand levels to identify the breakpoints. We focus on discrete demand formulation and choices and use a trip-based traffic simulator.This study analyzes the breakpoints for the solution of three popular equilibrium conditions: User equilibrium (UE), System optimum (SO) and Boundary Rational User Equilibrium (BRUE). First, we investigate breakpoints on a well-known network (Braess) in the static case in order to better define this concept. Second, breakpoints are investigated on a real network (Lyon, France) where dynamic travel times are provided by a microscopic traffic simulator. When the breakpoints are obtained for a given scenario, we focus on identifying demand ranges where some paths are not used in SO while being travelled in UE or BRUE. Following the concept of Braess paradox, this permits to design banning strategies at some key locations in the network to prevent some alternatives from being used and thus to improve the system performance. We show by simulation that such a strategy is effective, which demonstrates the importance of breakpoint identification.

Modeling of Precision Machining for Crankshaft Follow-up Grinder

In this paper, follow-up grinding of crankshaft is studied and the mathematical model of follow-up grinding motion is established. Taking the double grinding wheel crankshaft follow-up grinder as the research object, the motion errors of the machine tool are obtained by analyzing the motion relations among the moving bodies. Based on the kinematics theory of multi-body system, the kinematics model of the whole machine tool is established. The position matrix of any cutting point is described according to the kinematic chain of “bed-workpiece” and “bed-tool”, and the precise machining model of double grinding wheel follow-up grinding machine tool is established by using the coincidence principle of tool actual trajectory and tool path. The coordinate system of each moving body is established, the transformation matrix between moving bodies is obtained, and the precision machining model of double grinding wheel follow-up crankshaft CNC grinding machine is solved, which lays a foundation for error compensation of the machine.

Polynomial modelling of proton trajectories in homogeneous media for fast most likely path estimation and trajectory simulation

Protons undergo many small angle deflections when traversing a medium, such as a patient. This effect, known as multiple Coulomb scattering (MCS), leads to degraded image resolution in proton radiography and computed tomography (CT) and to lateral spreading of the dose distribution in proton therapy. To optimally account for MCS in proton imaging, the most likely path (MLP) of a proton is estimated based on its position and propagation angle measured in front of and behind the object. In this work, we propose a functional which quantifies the likelihood of a proton trajectory and study how it can be used to model proton trajectories in a homogeneous medium. We focus on two aspects: first, we present an analytical method to quickly generate proton trajectories in a homogeneous medium based on the likelihood functional and validate it through Monte Carlo simulations. It could be used for fast generation of proton CT images without a full Monte Carlo simulation, or potentially to complement the components in a treatment planning Monte Carlo which simulate MCS. Second, by maximising the likelihood functional, we derive an expression for the MLP which is equivalent to the conventional ones reported in the literature yet computationally more convenient. Moreover, we show that the MLP is strictly a polynomial function if the protons’ energy loss in the medium is approximated as a polynomial and that the orders of both are linked. We validate our MLP through Monte Carlo simulations and compare proton CT images reconstructed with our expression and with the conventional one. We find that an MLP polynomial of orders larger than five do not lead to increased spatial resolution compared to lower order expressions.

Active Scene Understanding via Online Semantic Reconstruction

AbstractWe propose a novel approach to robot‐operated active understanding of unknown indoor scenes, based on online RGBD reconstruction with semantic segmentation. In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene. Our algorithm is built on top of a volumetric depth fusion framework and performs real‐time voxel‐based semantic labeling over the online reconstructed volume. The robot is guided by an online estimated discrete viewing score field (VSF) parameterized over the 3D space of 2D location and azimuth rotation. VSF stores for each grid the score of the corresponding view, which measures how much it reduces the uncertainty (entropy) of both geometric reconstruction and semantic labeling. Based on VSF, we select the next best views (NBV) as the target for each time step. We then jointly optimize the traverse path and camera trajectory between two adjacent NBVs, through maximizing the integral viewing score (information gain) along path and trajectory. Through extensive evaluation, we show that our method achieves efficient and accurate online scene parsing during exploratory scanning.

System integration of a fluoroscopic image calibration using robot assisted surgical guidance for distal locking process in closed intramedullary nailing of femur

&lt;span&gt;Distal locking procedure is one of the most complex tasks in close intramedullary nailing operation which requires fluoroscopic image to interpret 2-D distal locking position on image related to 3-D distal locking position on the patient site. Hence the surgeon has to perform the distal locking process by using multiple fluoroscopic images which causes a lot of x-ray exposure to the patient and surgeon and is a time consuming task. This paper presents the system integration of a fluoroscopic image calibration using robot assisted surgical guidance. The system integration consists of three parts; distal locking recovery, fluoroscopic calibration and tracking, and robot assisted surgical guidance. The distal locking-hole recovery algorithm is based on characteristic information of the major and minor axes of distal locking hole. The fluoroscopic calibration and tracking is modeled as pin-hole projection model to estimate a projection equation based on optical tracking system. The robot-assisted surgical guidance is developed to overlay a trajectory path using a laser beam for reducing the problem of hand – eye coordination on most surgical navigation system. We integrate each part to complete a surgical navigation system for distal locking process. The experiment of system integration is conducted to validate the accuracy of distal locking axis position and orientation. The results of the system integration shows a mean angular error of 1.10 and mean Euclidean distance in X-Y plane error of 3.65 mm.&lt;/span&gt;

A Bionic Robot Navigation Algorithm Based on Cognitive Mechanism of Hippocampus

The firing of space cell in hippocampus is considered to be able to form an intrinsic map for the environment which is called cognitive map. Previous bionic navigation algorithms (such as rat simultaneous localization and mapping) and traditional SLAM algorithms lack sufficient physiological basis and cannot reflect the cognitive mechanism of hippocampal formation. Based on the cognitive mechanism of hippocampal space cells, this paper proposes a navigation algorithm for constructing accurate environmental cognitive map. This algorithm is characterized by the construction of a unified spatial cell attractor model for self-motion trajectory path integration. The expressions of grid cells and place cells are driven by stripe cells. The algorithm performs closed-loop detection by collecting depth image, red green blue+depthmap information and corrects the error of spatial cells’ path integral. Eventually, we get a precise cognitive map of the environment and bionic robot navigation is achieved by global navigation and local navigation algorithm based on the map. The cognitive map is a topological metric map that contains the topological relations of the environment feature point coordinates, visual cues, and specific sites. In this paper, the method is verified by the simulation experiment and the physical experiment on the robot platform. The research results laid the foundation for the research of the robot navigation method based on the hippocampus cognitive mechanism. Note to Practitioners —Environmental cognition and navigation ability are the main function of intelligent mobile robots. People and animals have strong adaptability and cognitive ability in unfamiliar environment, and they can independently recognize and navigate in unfamiliar environment. Now, the environmental cognition and navigation ability of intelligent robots are far from the level of human and animal. This paper suggests a bionic robot navigation algorithm based on the cognitive mechanism of rat hippocampus. The bionic robot navigation algorithm makes mobile robots more intelligent by learning and imitating human and animal’s environmental cognition and navigation ability. This navigation algorithm conforms to the physiological characteristics and is pretty accurate and intelligent. The experimental results demonstrate the effectiveness of this algorithm in building environment map and navigation.

Log-optimal and rapid paths in von Neumann-Gale dynamical systems

Von Neumann-Gale dynamical systems are defined in terms of multivalued operators in spaces of random vectors, possessing certain properties of convexity and homogeneity. A central role in the theory of such systems is played by a special class of paths (trajectories) called rapid: they grow over each time period [t−1,t] in a sense faster than others. The paper establishes existence and characterization theorems for such paths showing, in particular, that any trajectory maximizing a logarithmic functional over a finite time horizon is rapid. The proof of this result is based on the methods of convex analysis in spaces of measurable functions. The study is motivated by the applications of the theory of von Neumann-Gale dynamical systems to the modeling of capital growth in financial markets with friction.

A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors

The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.

Robust Motion Control of an Underactuated Hovercraft

In this paper, we address the tasks of trajectory tracking (TT) and path following (PF) for a hovercraft vehicle in the presence of uncertain parameters and unknown external disturbances. Building on the backstepping technique, the proposed TT (PF) control laws are able to drive a hovercraft toward and stay within a neighborhood of a reference trajectory (path), achieving global practical stability. Moreover, the devised control strategies also guarantee that the actuations remain bounded with respect to the position error. The controller is made robust to constant external disturbances and uncertain model parameters by the introduction of dynamic estimators for the disturbance and friction coefficients. A projection operator is used to ensure the estimates remain within prescribed bounds and are sufficiently smooth to be backstepped. In order to validate the efficacy and performance of the proposed controllers, we present and analyze both simulation and experimental results.

A software-in-the-loop implementation of adaptive formation control for fixed-wing UAVs

This paper discusses the design and software-in-the-loop implementation of adaptive formation controllers for fixed-wing unmanned aerial vehicles &#x0028 UAVs &#x0029 with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission &#x0028 e.g. depending on the payload &#x0029. Modelingg and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduPilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-in-the-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.

Estimation of Doppler Positioning for NavIC System in Static and Dynamic Conditions

The primary objective of any navigation system is to provide accurate user position. Navigation with Indian Constellation (NavIC) is an emerging regional satellite navigation system being developed by ISRO, India. The positional accuracy of the NavIC depends upon various parameters based on the application. Doppler shift is one among those parameters which plays an important role in finding the user position in dynamic conditions. The effect of the Doppler shift is more in high dynamic applications like missiles launching, air navigation due to high relative velocity between receiver and satellite. In this Paper, an efficient algorithm is developed to estimate the Doppler positioning using least squares method in static and various dynamic conditions. For this, the experimental data acquired from Indian Regional Navigation Satellite System (IRNSS)-GPS receiver located at low latitude station (Hyderabad: 17.39˚N, 78.31˚E) is used. A trajectory path has been simulated to estimate the user position and its accuracy measures in low and high dynamic conditions. It is noticed that, Doppler shift vary ±1KHz for geosynchronous satellites in static conditions, whereas it is ±40KHz in high dynamics. It is observed the position error is high in high dynamics as compared with low dynamics because of the higher Doppler shifts.