Trajectory Path Research Articles

Visual Navigation System for Autonomous Drone using Fiducial Marker Detection

Drones have been quickly developing for civilian applications in recent years. Because of the nonlinearity of the mathematical drone model, and the importance of precise navigation to avoid possible dangers, it is necessary to establish an algorithm to localize the drone simultaneously and maneuver it to the desired destination. This paper presents a visual-based multi-stage error tolerance navigation algorithm of an autonomous drone by a tag-based fiducial marker detection in finding its target. Dynamic and kinematic models of the drone were developed by Newton-Euler. The position and orientation of the drone, related to the tag, are determined by AprilTag, which is used as feedback in a closed-loop control system with an Adjustable Proportional-Integral-Derivative (APID) controller. Parameters of the controller are tuned based on steady-State error, which is defined as the distance of the drone from the desired point. The sequence of path trajectory, that drone follows to reach the desired point, is defined as a navigation algorithm. A model of the drone was simulated in a virtual outdoor to mimic hovering in complex obstacles environment. The results present satisfactory performance of the navigation system programmed by the APID controller in comparison with the conventional Proportional-Integral-Derivative (PID) controller. It can be ascertained that the proposed navigation system based on a tag marker in the closed-loop control system is applicable to maneuvering the drone autonomously and useful for various industrial tasks in indoor/outdoor environments.

АКМЕОЛОГІЧНИЙ АСПЕКТ ПРОФЕСІЙНОЇ ДІЯЛЬНОСТІ МАЙСТРІВ ВИРОБНИЧОГО НАВЧАННЯ

The article reveals the essence of the acmeological approach in the field of education, which is chosen to create conditions that encourage the individual to progressive self-development, self-organization and, accordingly, professional self-improvement in achieving the optimal level of professional development. The internal conditions for achieving professional acme of masters of industrial training are determined: positive motivation to achieve the expected results with a high level of demands and self-realization; focus on the ascending trajectory of the professional path; productive activity in performing professional functions; the desire to preserve and increase their achievements; the ability to mobilize potential opportunities (motivational, intellectual, operational, emotional and volitional) and recover from physical and psychological stress. The external conditions for the emergence of acme masters of industrial training are determined: assistance in mastering the means necessary for the development of pedagogical thinking, creativity, individuality of the personality and his spiritual potential; ensuring the implementation of personally and socially significant prospects in professional activities; stimulating the process of self-improvement; strengthening the integration role of acme-psychological support as a holistic and continuous process of study, analysis, formation, development, self-development and correction of the specialist's personality; development and realization of the corresponding maintenance, models, algorithms of acmeological technologies, adequate means of methodical maintenance, diagnostics and assessment of the professional developmentdynamics. The tools of accumulation of professional activityresults in the context of acme are characterized. In particular, the acmeogram, which indicates the types of professional activities and personality qualities that lead not only to the masters of industrial training socially necessary results, but also provide progressive development and professional development, promotion to high levels of professionalism; portfolio as a description in any form of educational and professional achievements of industrial trainingmasters, which includes information on the main stages of activity, professional development, including the achieved results, information on participation in projects, publications, methodological developments, etc. Key words: acmeology, master of industrial training, vocational education institution.

Channel Propagation Characteristics on the Performance of 4G Cellular Systems from High Altitude Platforms (HAPs)

In this paper, we investigated the effect of different channel propagation characteristics on the performance of 4G systems from high altitude platforms (HAPs). The use of High-Altitude Platforms for communication purpose in the past focused mostly on the assumption that the platform is quasi stationary. The technical limitation of the assumption was that of ensuring stability in the positioning of the platform in space. The use of antenna steering and other approaches were proposed as a solution to the said problem. In this paper, we proposed a channel model which account for the motion of the platform. This was done by investigating the effect of Doppler shift on the carrier frequency as the signals propagate between the transmitter and receiver while the High-Altitude Platform is in motion. The basic free space model was used and subjected to the frequency variation caused by the continuous random shift due to the motion of the HAPs. The trajectory path greatly affects the system performance. A trajectory of 30km, 100km and 500km radii were simulated. An acute elevation angle was used in the simulation. The proposed model was also compared to two other channel models to illustrate its performance. The results show that the proposed model behave similar to the existing models except at base station ID 35 and 45 where the highest deviation of 20dBm was observed. Other stations that deviated were less than 2dBm.

Integrated path planning and trajectory tracking control for quadrotor UAVs with obstacle avoidance in the presence of environmental and systematic uncertainties: Theory and experiment

This paper proposes an innovative integrated path planning and trajectory tracking control framework for a quadrotor unmanned aerial vehicle (UAV) in the presence of environmental and systematic uncertainties to achieve integrated guidance and control. Firstly, in order to perform real-time path planning, a computationally cost-effective planning algorithm is designed to find an optimal and smooth path while avoiding both static and dynamic obstacles. Then, by employing the pure-pursuit path following approach, the generated geometric path is converted to a trajectory profile related to time, which serves as the reference commands for the low-level trajectory tracking controller. Finally, a novel adaptive sliding mode trajectory tracking controller is proposed to compensate model uncertainties and maintain the desired tracking performance for the studied quadrotor UAV. With the proposed adaptive schemes, overestimation of uncertain parameters can be avoided, which further contributes to avoiding control chattering of the system. The performance of the proposed framework is validated through comparative simulation and experimental tests based on a quadrotor UAV subject to model uncertainties and environmental obstacles, which confirms the effectiveness and superiority of the proposed approach for practical applications.

Mixed-mode tensile/shear fracture of the additively manufactured components under dynamic and static loads

In the practical implementation of the Additively Manufactured (AM) construction in engineering designs, Fused Deposition Modeling (FDM) is recently used to manufacture the inexpensive Acrylonitrile Butadiene Styrene (ABS) parts. The cracking behaviors of such layered components are inspected using the Semi-Circular Bending (SCB) fracture samples. In particular, the effect of anisotropy or layered nature of 3D printed specimens is only considered on the fracture manner among the affecting parameters. The dynamic and static three-point bend tests are conducted from pure mode I to pure mode II conditions. Dynamic experiments are performed using a modified Charpy instrument, and the required energies for the crack initiation are obtained. In the next step, a finite element model based on the Equivalent Material Concept-Generalized Maximum Tangential Stress (EMC-GMTS) failure theory is introduced, and its predictions are compared with the obtained experimental data. Under different loading rates, the crack path trajectories and fracture behavior is surveyed in detail concerning the isotropic counterparts in two micro and macro scales. According to the SEM images and the validity of the brittle fracture theory (with a maximum of 5% error), it is proved that the SCB samples made from ABS are fractured in a brittle manner. The fracture behavior of the FDM 3D-printed structures under dynamic loading conditions is analogous to those homogenous materials, especially where the mode I deformation is dominant. Also, the dynamic and static paths for dominantly pure mode II loading conditions are nearly identical.

{text{COSNet}}_i: ComplexOme-Structural Network Interpreter used to study spatial enrichment in metazoan ribosomes

BackgroundUpon environmental stimuli, ribosomes are surmised to undergo compositional rearrangements due to abundance changes among proteins assembled into the complex, leading to modulated structural and functional characteristics. Here, we present the ComplexOme-Structural Network Interpreter ({text{COSNet}}_i), a computational method to allow testing whether ribosomal proteins (rProteins) that exhibit abundance changes under specific conditions are spatially confined to particular regions within the large ribosomal complex.Results{text{COSNet}}_i translates experimentally determined structures into graphs, with nodes representing proteins and edges the spatial proximity between them. In its first implementation, {text{COSNet}}_i considers rProteins and ignores rRNA and other objects. Spatial regions are defined using a random walk with restart methodology, followed by a procedure to obtain a minimum set of regions that cover all proteins in the complex. Structural coherence is achieved by applying weights to the edges reflecting the physical proximity between purportedly contacting proteins. The weighting probabilistically guides the random-walk path trajectory. Parameter tuning during region selection provides the option to tailor the method to specific biological questions by yielding regions of different sizes with minimum overlaps. In addition, other graph community detection algorithms may be used for the {text{COSNet}}_i workflow, considering that they yield different sized, non-overlapping regions. All tested algorithms result in the same node kernels under equivalent regions. Based on the defined regions, available abundance change information of proteins is mapped onto the graph and subsequently tested for enrichment in any of the defined spatial regions. We applied {text{COSNet}}_i to the cytosolic ribosome structures of Saccharomyces cerevisiae, Oryctolagus cuniculus, and Triticum aestivum using datasets with available quantitative protein abundance change information. We found that in yeast, substoichiometric rProteins depleted from translating polysomes are significantly constrained to a ribosomal region close to the tRNA entry and exit sites.Conclusions{text{COSNet}}_i offers a computational method to partition multi-protein complexes into structural regions and a statistical approach to test for spatial enrichments of any given subsets of proteins. {text{COSNet}}_i is applicable to any multi-protein complex given appropriate structural and abundance-change data. {text{COSNet}}_i is publicly available as a GitHub repository https://github.com/MSeidelFed/COSNet_i and can be installed using the python installer pip.

Effects of dinoflagellate Gymnodinium catenatum on swimming behavior and expression of heat shock protein (hsp) genes in the brine shrimp Artemia franciscana

To understand the effects of the toxic marine dinoflagellate, Gymnodinium catenatum, on the brine shrimp, Artemia franciscana, we examined the acute toxicity and swimming behavior parameters such as swimming speed, swimming distance, and swimming path trajectory with transcriptional regulation of heat shock protein (hsp) genes in response to G. catenatum exposure. Mortality was not observed in response to G. catenatum. In the case of swimming behavior parameters, swimming speed and swimming distance were significantly decreased (P<0.05) for 5min at three concentrations (240, 360, and 600cells/mL) of G. catenatum, whereas no significant change in swimming path trajectory was observed, suggesting that G. catenatum has potential adverse effects on the swimming behavior of A. franciscana. Additionally, the four A. franciscana-hsp genes (hsp26, hsp40, hsp70, and hsp90) were upregulated in response to G. catenatum. In particular, A. franciscana-hsp40 was significantly upregulated in response to 600 cells/mL G. catenatum, suggesting that A. franciscana-hsp genes are highly associated with cellular defense mechanisms and that A. franciscana-hsp40 is a potential biomarker for G. catenatum exposure. Overall, this study improves our understanding of the effects of G. catenatum on the swimming behavior and cellular defense mechanisms of A. franciscana.

A pilot study of new approaches to exploring illness trajectories and patterns of comorbidity in major mental disorders.

We explored lifetime comorbidities in clinical subsamples with a diagnosis of Psychosis (N=143), bipolar (BD=511), and unipolar disorders (UP=861). We analyzed trajectories and patterns of comorbidities using novel metrics, namely bubble plots and density of antecedent events per year of illness exposure per individual. Age at onset (AAO) of most comorbidities was similar to epidemiological studies, but cumulative rates were higher in clinical cases. There were some between group differences in patterns or burden of comorbidities, for example, Psychosis showed the earliest AAO of any mental disorder; UP showed the latest AAO of the index diagnosis. The relative risk of multimorbidity was lower in UP compared with other diagnoses, however, the goodness of fit for the illness trajectory path was lowest for BD. Bubble plots offer a useful representation of timing, sequence, cumulative probability and of comorbidities, the added value of reporting density measures was less obvious.

Motion Planning for Vibration Reduction of a Railway Bridge Maintenance Robot with a Redundant Manipulator

Motivated by the potential applications of maintenance and inspection tasks for railway bridges, we have developed a biped climbing robot. The biped climbing robot can climb on the steel guardrail of the railway bridge with two electromagnetic feet and implement the maintenance and inspection tasks by a redundant manipulator with 7 degrees of freedom. To reduce the vibration of the manipulator caused by the low rigidity of the guardrail and the discontinuous trajectories of joints, a motion planning algorithm for vibration reduction is proposed in this paper. A geometric path accounting for obstacle avoidance and the manipulator’s center of gravity is determined by the gradient projection method with a singularity-robust inverse. Then, a piecewise quintic polynomial S shape curve with a smooth jerk (derivative of joint angular acceleration) profile is used to interpolate the sequence of joint angular position knots that are transformed from the via-points in the obstacle-avoidance path. The parameters of the quintic polynomial S-curve are determined by a nonlinear programming problem in which the objective function is to minimize the maximus of the torque exerted by the manipulator on the guardrail throughout the jerk-continuous trajectory. Finally, a series of simulation experiments are conducted to validate the effectiveness of the proposed algorithm. The simulation results show that the tracking errors of the trajectory with the proposed optimization algorithm are significantly smaller than the tracking errors of the trajectory without optimization. The absolute values of mean deviation of the tracking errors of the three coordinate axes decreased by at least 48.3% compared to the trajectory without vibration-reduction in the triangle working path and linear working path trajectory following simulations. The analysis results prove that the proposed algorithm can effectively reduce the vibration of the end effector of the manipulator.

Changes of Mind after Movement Onset Depend on the State of the Motor System.

Decision-making is traditionally described as a cognitive process of deliberation followed by commitment to an action choice, preceding the planning and execution of the chosen action. However, this is challenged by recent data suggesting that during situated decisions, multiple options are specified simultaneously and compete in premotor cortical areas for selection and execution. Previous studies focused on the competition during planning and left unaddressed the dynamics of decisions during movement. Does deliberation extend into the execution phase? Are nonselected options still considered? Here we studied a decision-making task in which human participants were instructed to select a reaching path trajectory from an origin to a rectangular target, where reward was distributed nonuniformly at the target. Critically, we applied mechanical perturbations to the arm during movement to study under which conditions such perturbations produce changes of mind. Our results show that participants initially selected the direction of movement toward the highest reward region and changed their mind most frequently when the two choices offered the same reward, showing that deliberation continues and follows cost–benefit considerations during movement. Furthermore, changes of mind were dependent on the intensity of the perturbation and the current state of the motor system, including velocity and distance to targets. Although reward remains most relevant, our results indicate that the state of the motor system when the perturbation occurs is a crucial determinant of changes of mind.

Revisiting Stewart–Gough platform applications: A kinematic pavilion

Stewart–Gough platforms are well known for their extraordinary kinematic motion and therefore they are widely used as devices, ranging from flight simulators to microsurgical manipulators. However, they have not yet been explored much as architectural objects and transformable spaces with regards to irregular arrangements of legs and their associate structural performance. In the current study, an innovative architectural and structural application of the Stewart–Gough platform, implemented as full-scale kinematic pavilion, namely the Zero Gravity pavilion, at Aalto University, Finland, is presented. During the design process a Stewart–Gough 3–3 configuration was rearranged to an irregular 6–6 configuration. The architectural freedom in the arrangement of columns was guided by its immanent effect on the structure’s motion, stability, and strength. We opted for one telescopic leg only and its selection is based on four main criteria. Firstly, for each telescopic leg the stability of the different configurations is investigated. Secondly, the self-collision of leg–leg, leg–roof, and roof–floor was investigated by means of physical and computational models as well as through the full-scale pavilion. Thirdly, the selection process is influenced by the force distribution on the six legs. Fourthly, the path trajectory of the kinematic structure is examined in terms of magnitude and type of motion as an architectural feature. The final choice of the telescopic leg was based on the conclusions drawn from the parametric architectural and structural studies. The overall spatial and structural qualities of the system was validated by the full-scale Zero Gravity pavilion.

Research on Mobile User Interface for Robot Arm Remote Control in Industrial Application

The mobile interfaced robot arms are majorly being used nowadays in order to provide the remote-control applicability for various industrial and manufacturing applications. This article proposes a robotic arm platform for controlling the industrial application. The proposed system includes various modules like a robot arm, a controller module and a remote mobile operating application for visualizing the robot arm angles having real time applicability. Augmented reality (AR) is utilized for robot control WIFI communication and the robot angle information is obtained for varying real time environment. This novel approach incorporated the AR technology into mobile application which allow the real time virtual coordination with physical platform. The feasible trajectories are generated using the proposed methodology and a comparison is made between the desired and real trajectory paths. The simulation results are obtained for various assessment indicators and effectual outcomes are achieved with 98.03% accuracy value and 0.185, 0.180 of error and loss values for training phase. The accuracy value of 97.65% is achieved for testing phase with corresponding 0.209 and 0.190 minimum error and loss values. The proposed platform provides the feasible and reliable outcomes in the real time environment for real time manufacturing industry applications.

Performance Estimation of a Wireless Sensor Network with a Mobile Sink Moving in Different Trajectories at Different Velocities

Background: Throughout the past few years, numerous Medium Access Control (MAC) protocols, routing protocols, node deployment mechanisms and duty cycle variation schemes have been designed for achieving high throughput, low delay and jitter, and long network lifetime in Wireless Sensor Networks (WSNs). In a WSN with static sink, voluminous sensors transmit their sensed data to the sink node. The coordinators mutually present in the range of sensors and sink have to forward a number of packets, which cause rapid depletion of their battery. These coordinators become dead too early resulting in the breakage of the communication channel and formation of energy holes. However, to save energy with a static sink, the duty cycle should be short. A mobile sink is a better option than a static sink if the duty cycle is long, as it balances energy consumption among the sensors. It is well observed that the mobile sink is capable of acquiring homogeneous energy depletion leading to stretched lifetime enhancing network performance. Methods: The vital benefaction of this paper is to present a simulation-based analysis of the network performance with a mobile sink having different trajectories of path traversed at different velocities. The intent is to find out the most appropriate and efficient trajectory and a particular velocity for a specific WSN with 100 nodes. The terrain area of the network is 210×210 m2 with the communication range of 20 m. The routing, network and MAC protocols implemented are Ad hoc On-Demand Distance Vector (AODV), Internet Protocol version 4 (IPv4) and Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 respectively. This paper has evaluated and analyzed the influence of lawn mower, elliptical and circular trajectories of a mobile sink moving at different velocities of 0.5, 1 and 2 m/s. The optimum performance is achieved at the velocity of 2 m/s for a circular trajectory of the mobile sink. It is observed that performance has significantly varied with the variation of trajectories and velocities. The notion of precise utilization of sink mobility improves the performance than a static sink. It is equally important to determine the most effective mechanism to implement mobile sinks and to find out the most appropriate scheme out of them. Results: The attainment parameters just as total messages received, average end to end delay (seconds), jitter (seconds), throughput (bits per second), number of packets dropped, number of packets dropped due to channel access failure, residual battery (mAh) and network lifetime (hours) for different trajectories such as lawn mower, elliptical and circular at different speeds of 0.5, 1 and 2 m/s of the sink node are evaluated and compared. The simulation results present that the circular trajectory and the velocity of 2 m/s have provided optimum performance. Conclusion: The objective was to precisely analyze and evaluate the influence of different trajectories of a mobile sink moving at different velocities in a WSN of 100 nodes to determine the most effective and appropriate trajectory and velocity to optimize the attainments. The intent is to uniform the power exhaustion amidst the sensors. The purpose was to gain the attention of researchers of this field to significantly contribute to novel research.

Nonlinear Filter and Neural Modeling for Calibration of Aircraft Airdata System

Calibration of aircraft airdata system deals with the reconstruction of flight path trajectories from the noisy flight data using six-degree-of-freedom equations of aircraft. Aircraft system dynamics are highly nonlinear in rapid variations of the aircraft motion and require the use of a nonlinear filtering algorithm. In this paper, a methodology based on data-driven decision making is introduced to obtain the accurate values of aircraft flow angles (angle of attack and angle of sideslip) and static pressure from its noisy measurements. For this, the integration of fault detection and isolation approach to the adaptive nonlinear filter is applied to dynamic maneuvers, and a neural model of calibration function is established over a flight envelope using the filter estimates. A deterministic airdata calibration function is derived by estimating its coefficients from the established neural model using the neural partial differentiation method. The cascading impact of adaptive estimation and neural modeling of airdata calibration function reduces the development cost of an aircraft. The investigations are initially made on simulated flight data under various conditions of wind and turbulence and later extended to the flight data of aircraft to identify the calibration function valid over a flight envelope. The complementary flight data are used to validate the calibration function and are compared with online estimation results of the robust filter. The experimental results show that the proposed algorithm can isolate and rectify the fault and exhibits more accurate estimates directly with neural modeling than the nonadaptive version of the filter.

On Line Threat Computation For Unmanned Air Vehicles. (Dept. E)

Unmanned Air Vehicles (UAVs) have potential strengths to be implemented in the battle fields. A major problem for UAVs is to plan an optimal trajectory path from its starting position to the target position in real time. For a path to be optimal it has to minimize: threat, path length, fuel consumption, flying time, and preserves dynamic constructs of the vehicle.

Using density of antecedent events and trajectory path analysis to investigate family-correlated patterns of onset of bipolar I disorder: a comparison of cohorts from Europe and USA

BackgroundMajor contributors to the global burden of bipolar disorders (BD) are the early age at onset (AAO) and the co-occurrence of non-mood disorders before and after the onset of BD. Using data from two independent cohorts from Europe and the USA, we investigated whether the trajectories of BD-I onset and patterns of psychiatric comorbidities differed in (a) individuals with or without a family history (FH) of BD, or (b) probands and parents who both had BD-I.MethodsFirst, we estimated cumulative probabilities and AAO of comorbid mental disorders in familial and non-familial cases of BD-I (Europe, n = 573), and sex-matched proband-parent pairs of BD-I cases (USA, n = 194). Then we used time to onset analyses to compare overall AAO of BD-I and AAO according to onset polarity. Next, we examined associations between AAO and polarity of onset of BD-I according to individual experiences of comorbidities. This included analysis of the density of antecedent events (defined as the number of antecedent comorbidities per year of exposure to mental illness per individual) and time trend analysis of trajectory paths plotted for the subgroups included in each cohort (using R2 goodness of fit analysis).ResultsEarlier AAO of BD-I was found in FH versus non-FH cases (log rank test = 7.63; p = 0.006) and in probands versus parents with BD-I (log rank test = 15.31; p = 0.001). In the European cohort, AAO of BD-I was significantly associated with factors such as: FH of BD (hazard ratio [HR]: 0.60), earlier AAO of first non-mood disorder (HR: 0.93) and greater number of comorbidities (HR: 0.74). In the USA cohort, probands with BD-I had an earlier AAO for depressive and manic episodes and AAO was also associated with e.g., number of comorbidities (HR: 0.65) and year of birth (HR: 2.44). Trajectory path analysis indicated significant differences in density of antecedents between subgroups within each cohort. However, the time trend R2 analysis was significantly different for the European cohort only.ConclusionsEstimating density of antecedent events and comparing trajectory plots for different BD subgroups are informative adjuncts to established statistical approaches and may offer additional insights that enhance understanding of the evolution of BD-I.

Inference of high-resolution trajectories in single-cell RNA-seq data by using RNA velocity

SummaryTrajectory inference (TI) methods infer cell developmental trajectory from single-cell RNA sequencing data. Current TI methods can be categorized into those using RNA velocity information and those using only single-cell gene expression data. The latter type of methods are restricted to certain trajectory structures, and cannot determine cell developmental direction. Recently proposed TI methods using RNA velocity information have limited accuracy. We present CellPath, a method that infers cell trajectories by integrating single-cell gene expression and RNA velocity information. CellPath overcomes the restrictions of TI methods that do not use RNA velocity information: it can find multiple high-resolution trajectories without constraints on the trajectory structure, and can automatically detect the direction of each trajectory path. We evaluate CellPath on both real and simulated datasets and show that CellPath finds more accurate and detailed trajectories than the state-of-the-art TI methods using or not using RNA velocity information.

Digital Communication: a technology of trust marketing

The paper represents the review of marketing management tools and technologies online: the concept of trust funnel, web-traffic temperature, digital marketing tools. The relevance of the work is determined by the following factors: first, globalization and digital revolution have irreversibly changed the trajectory of the marketing technology development path. Mass advertising has smoothly lost its influence, and companies began to focus more on the customer. The emergence of new digital media has led to new concept – digital marketing. Second, many organizations are using a combination of traditional and digital marketing channels; however, digital marketing is becoming more prominent as it allows for more precise tracking of resources and funds in relation to other traditional marketing channels. In conclusion, the authors highlight common elements in defining the concept of digital marketing: its connection with technological progress and the use of the Internet, leading us to social media. In the new digital age, the main function of marketing is to be in constant contact with users, customers, the community and other companies, provides relevant news and content that convey unique experiences, communicate with people, giving them the opportunity to interact with the company or brand.

Design and validation of simple bend beam specimen for covering the full range of I+II fracture modes

Using short beam specimen containing an edge crack (perpendicular to the beam axis) and subjected to asymmetric three-point bend loading a new test configuration (called ASBB) was suggested for investigating the mixed mode I/II fracture. Despite the conventional beam specimen with high aspect ratio of length to width that is not able to produce mode II or dominantly mode II conditions, complete mode mixities were obtained using the proposed three-point bend asymmetric short beam specimen. The fracture parameters including modes I and II stress intensity factors and T-stress were determined numerically for this test specimen with different crack lengths and bottom rollers distances relative to the crack. The practical ability of the ASBB specimen was examined experimentally by conducting several mixed-mode I/II fracture tests on PMMA material. The critical stress intensity factors, the direction of fracture kinking and the path of fracture trajectory were investigated both experimentally and theoretically using MTS and GMTS criteria. The fracture toughness of PMMA tested with the ASBB specimen was increased by increasing the contribution of mode II component. The effects of beam length aspect ratio, crack type and loading type on the mixed mode fracture of cracked beam samples subjected to three-point bend loading were also examined.

A Hierarchical Autonomous Driver for a Racing Car: Real-Time Planning and Tracking of the Trajectory

The aim of this study was to develop trajectory planning that would allow an autonomous racing car to be driven as close as possible to what a driver would do, defining the most appropriate inputs for the current scenario. The search for the optimal trajectory in terms of lap time reduction involves the modeling of all the non-linearities of the vehicle dynamics with the disadvantage of being a time-consuming problem and not being able to be implemented in real-time. However, to improve the vehicle performances, the trajectory needs to be optimized online with the knowledge of the actual vehicle dynamics and path conditions. Therefore, this study involved the development of an architecture that allows an autonomous racing car to have an optimal online trajectory planning and path tracking ensuring professional driver performances. The real-time trajectory optimization can also ensure a possible future implementation in the urban area where obstacles and dynamic scenarios could be faced. It was chosen to implement a local trajectory planning based on the Model Predictive Control(MPC) logic and solved as Linear Programming (LP) by Sequential Convex Programming (SCP). The idea was to achieve a computational cost, 0.1 s, using a point mass vehicle model constrained by experimental definition and approximation of the car’s GG-V, and developing an optimum model-based path tracking to define the driver model that allows A car to follow the trajectory defined by the planner ensuring a signal input every 0.001 s. To validate the algorithm, two types of tests were carried out: a Matlab-Simulink, Vi-Grade co-simulation test, comparing the proposed algorithm with the performance of an offline motion planning, and a real-time simulator test, comparing the proposed algorithm with the performance of a professional driver. The results obtained showed that the computational cost of the optimization algorithm developed is below the limit of 0.1 s, and the architecture showed a reduction of the lap time of about 1 s compared to the offline optimizer and reproducibility of the performance obtained by the driver.