17 research outputs found

    Adaptive Washout Filter Based on Fuzzy Logic for a Motion Simulation Platform With Consideration of Joints Limitations

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    Motion simulation platforms (MSPs) are widely used to generate driving/flying motion sensations for the users. The MSPs have a restricted workspace area due to the dynamical and physical restrictions of the Motion Platforms active joints as well as the physical limitations of its passive joints. The motion cueing algorithm (MCA) is the reproduction of the motion signal including linear accelerations and angular velocities. It aims to simultaneously respect the MSP's workspace limitations and make the same motion feeling for the user as a real vehicle. The Classical washout filter (WF) is a well-known type of MCA. The classical WF is easy to set-up, offers a low computational burden and high functionality but has some major drawbacks such as fixed WF parameters tuned according to worst-case scenarios and no consideration of the human vestibular system. As a result, adaptive WFs were developed to consider the human vestibular system and enhance the efficiency of the method using time-varying filters. The existing adaptive WFs only cogitate the boundaries of the end-effector in the Cartesian coordinate space as a substitute for the active and passive joints limitations, which is MSP's main limiting factor. This conservative assumption reduces the available workspace area of the MSP and increases the motion sensation error for the MSPs user. In this study, a fuzzy logic-based WF is developed, to consider the dynamical and physical boundaries of the active joints as well as the physical boundaries of the passive joints. A genetic algorithm is used to select the membership functions values of the active and passive joints boundaries. The model is designed using MATLAB /Simulink and the outcomes demonstrate the efficiency of the proposed method versus existing adaptive WFs

    Motion cueing in driving simulators for research applications

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    This research investigated the perception of self-motion in driving simulation, focussing on the dynamic cues produced by a motion platform. The study was undertaken in three stages, evaluating various motion cueing techniques based on both subjective ratings of realism and objective measures of driver performance. Using a Just Noticeable Difference methodology, Stage 1 determined the maximum perceptible motion scaling for platform movement in both translation and tilt. Motion cues scaled by 90% or more could not be perceptibly differentiated from unscaled motion. This result was used in Stage 2‟s examination of the most appropriate point in space at which the platform translations and rotations should be centred (Motion Reference Point, MRP). Participants undertook two tracking tasks requiring both longitudinal (braking) and lateral (steering) vehicle control. Whilst drivers appeared unable to perceive a change in MRP from head level to a point 1.1m lower, the higher position (closer to the vestibular organs) did result in marginally smoother braking, corresponding to the given requirements of the longitudinal driving task. Stage 3 explored the perceptual trade-off between the specific force error and tilt rate error generated by the platform. Three independent experimental factors were manipulated: motion scale-factor, platform tilt rate and additional platform displacement afforded by a XY-table. For the longitudinal task, slow tilt that remained sub-threshold was perceived as the most realistic, especially when supplemented by the extra surge of the XY-table. However, braking task performance was superior when a more rapid tilt was experienced. For the lateral task, perceived realism was enhanced when motion cues were scaled by 50%, particularly with added XY-sway. This preference was also supported by improvements in task accuracy. Participants ratings were unmoved by changing tilt rate, although rapid tilt did result in more precise lane control. Several interactions were also observed, most notably between platform tilt rate and XY-table availability. When the XY-table was operational, driving task performance varied little between sub-threshold and more rapid tilt. However, while the XY-table was inactive, both driving tasks were better achieved in conditions of high tilt rate. An interpretation of these results suggests that without the benefit of significant extra translational capability, priority should be given to the minimisation of specific force error through motion cues presented at a perceptibly high tilt rate. However, XY-table availability affords the simulator engineer the luxury of attaining a slower tilt that provides both accurate driving task performance and accomplishes maximum perceived realism

    CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis

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    This paper proposes transferred initialization with modified fully connected layers for COVID-19 diagnosis. Convolutional neural networks (CNN) achieved a remarkable result in image classification. However, training a high-performing model is a very complicated and time-consuming process because of the complexity of image recognition applications. On the other hand, transfer learning is a relatively new learning method that has been employed in many sectors to achieve good performance with fewer computations. In this research, the PyTorch pre-trained models (VGG19\_bn and WideResNet -101) are applied in the MNIST dataset for the first time as initialization and with modified fully connected layers. The employed PyTorch pre-trained models were previously trained in ImageNet. The proposed model is developed and verified in the Kaggle notebook, and it reached the outstanding accuracy of 99.77% without taking a huge computational time during the training process of the network. We also applied the same methodology to the SIIM-FISABIO-RSNA COVID-19 Detection dataset and achieved 80.01% accuracy. In contrast, the previous methods need a huge compactional time during the training process to reach a high-performing model. Codes are available at the following link: github.com/dipuk0506/SpinalNe

    Driving Simulator Motion Cueing Assessment: A Platform Design Perspective

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    The overall aim of this thesis was to study the effects of a simulator’s motion system on vestibular motion cueing fidelity in different contexts, evaluated in terms of drivers’ perception and behaviour, in low and high road friction conditions. The effects of manipulating the motion cueing algorithm (MCA), was found to be a function of the vehicle motion in a manoeuvre, and significant effects were observed. The applicability of simulators for the assessment of vehicle driven attribute qualities such as ride, steering and handling were studied by manipulating vehicle ride height (RH). The differences between the RHs were subjectively distinguishable by the drivers in the simulator. Incongruities between the subjective preferences and objective performances were observed in both of the independent comparisons of the MCAs and RHs. The effects of motion platform (MP) workspace size were found to be dependent on the manoeuvres and road friction level. In the low-friction condition, with the increase of MP size, two opposite effects were observed on drivers’ preferences and their performances, depending on the manoeuvre. In high-friction, in most of the handling and steering qualities, a direct relation was found between the MP size and appropriate vehicle RH. Furthermore, the optimal tuning of the MCAs and optimisation of the MP workspace size was introduced. A conservative motion cueing fidelity criteria was defined. A multi-layered optimisation method was developed that uses the optimal setting of the MCA, to address the MP translational workspace size, and to meet the fidelity criteria; applicable for different manoeuvres. This method was tested on the drivers’ performance data collected from the experiments in the simulator

    Development and application of smart actuation methods for vehicle simulators

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    Driving simulators are complex virtual reality systems that integrate visual displays, sound rendering systems, motion platforms, and human-machine-interface devices. They are used in different research areas and consequently, different studies are conducted using these systems, in conditions that would not be safe to be carried out in the real world. However, driving simulators are very expensive research tools. When building such a system, a compromise usually has to be made. Although a driving simulator cannot reproduce 1:1 real life situations or sensations because of its limitations, researchers still need to use such a device for training and research purposes, due to the realistic driving experience it has to offer to its driver. This work focuses on developing a three-degrees of freedom Essential Function Driving Simulator that integrates cost and design constraints, the human perception of motion and real vehicle motion achieved through simulated vehicle models, and the classical motion cueing strategy. The goal is, on the first hand, to immerse the driver to a certain extend into the simulation environment by using this virtual reality device and, on the second hand, to investigate the degree of realism of such a solution. Different actuation solutions are modelled and discussed in this research, with respect to the available workspace, singularity configurations, the system’s behaviour and the maximum forces needed in the frame of the overall cost constraints. A solution was chosen following kinematical and dynamical analyses, as a trade off solution among the above mentioned constraints. The human body finds itself in continuous movement and interaction with the environment. Motion is sensed by the human being through the vestibular system and the skin. The human motion perception mechanisms are mathematically modelled and studied, in order to apply their characteristics in the three-degrees of freedom driving simulator. Due to the limited workspace and degrees of freedom of the discussed simulator, the motion of the simulated vehicle cannot be identically reproduced by the motion system. Thus, special algorithms are designed to transform the motion of the vehicle model in achievable positions for the three actuators, and additionally, to render correct motion cues. The influence of the three variable parameters on the overall subjective degree of freedom is investigated using an optimisation method. The studied parameters are: motion, optical flow and haptic response, introduced by using a lane departure warning assistance system. It is shown in this research that the influence of motion cues on the subjective degree of realism rated by the drivers is of 84%. The vibrations in the steering wheel improve the realism of the simulation and have a 15% impact. The participants of these experiments could easily adapt to the provided assistance system and their immersion in the simulated environment was significantly influenced by the activation of the lane departure warning option. It has also been shown that drivers rated the motion and the accelerations felt in the simulator with 70.41%, compared to the experience of driving a real vehicle. These results are interpreted in this research by putting the emphasis on the fact that irrespective of the DOF of the actuation mechanism, a motion driving simulator should provide correct motion cues. The development of the vehicle models and of the motion cueing algorithms should be approached, so that the system provides motion as similar as possible to the real vehicle, as it is further discussed here.Entwicklung und Anwendung von intelligenten Ansteuerungsmethoden für Fahrzeugsimulatoren Fahrsimulatoren sind Virtual-Reality Systeme, die aus geeigneten Mensch-Maschinen-Schnittstellen, optische und akustische Wiedergabe und, wenn das Bedarf besteht, aus einen Bewegungsapparat bestehen. Sie werden in unterschiedlichen Forschungsfeldern verwendet um verschiedene Studien durchzuführen. Unter anderem können dadurch Manöverstudien durchgeführt werden, die in realen Fahrsituationen zu gefährlich für den Fahrer wären. Der Bau komplexer und hochauflösender Fahrsimulationen ist jedoch sehr Kostenintensiv. Obwohl ein Fahrsimulator die in realen Fahrsituationen empfundenen Fahrgefühle nicht originalgetreu wiedergegeben kann, durch den begrenzten Arbeitsraum, eignet sich ein solches Gerät zu Lehr- und Forschungszwecken. Diese Arbeit befasst sich mit der Entwickelung eines kostengünstigen Fahrsimulators mit drei Freiheitsgraden, der durch eine geeignete Motion-Cueing Strategie dem Fahrer ein ausreichendes Fahrgefühl widergibt. Es werden verschiedene Aktuierungslösungen in Bezug auf den begrenzten Arbeitsraum, singulären Stellungen, des maximalen Kraftbedarfs modelliert, verglichen und diskutiert. Es wurde eine Kompromisslösung gefunden basierend auf der kinematischen und dynamischen Analyse, die diese Begrenzungen berücksichtigt. Der menschliche Körper befindet sich in einer kontinuierlichen Bewegung und interagiert dabei mit der Umgebung. Die Bewegung wird durch das Vestibularorgan und durch die Haut wahrgenommen. Die menschliche Wahrnehmung wird durch ein geeignetes mathematisches Modell widergegeben. Der Bewegungsablauf des Fahrsimulators wurde unter Berücksichtigung der menschlichen Wahrnehmung ausgelegt und untersucht. Wegen dem begrenztem Arbeitsraum und der geringen Anzahl von Systemfreiheitsgraden kann der Simulator die reelle Fahrdynamik nicht im vollen Umfang an die Testperson weitergeben. Deshalb werden angepasste Algorithmen entwickelt um den Bewegungsablauf beschränkt durch drei Aktuatoren in einem akzeptablem umfang widerzugeben. Der Einfluss der drei Aktuatorparameter auf den Bewegungsablauf wird durch geeignete Optimierungsmethoden untersucht. Die Größen die anschließend durch das Fahrsimulator Setup untersucht werden sind unter anderem der Bewegungsablauf, die optische Darstellung und die haptische Wiedergabe. Die Wichtigkeit der empfundenen Fahrbewegung wurde durch die Probanden, im Vergleich zu einem statischen Fahrsimulator, mit 84% bewertet. Die Vibrationen im Lenkrad erhöhen das Realitätsempfinden um 15%. Die Testpersonen konnten sich schnell an die aktuierten Fahrsimulation anpassen und auch Assistenzsysteme wie Spurhalteassistent benutzen. Es wurde gezeigt, dass die im Fahrsimulator gefühlten Beschleunigungen zu ca. 70% an die im realen Fahrbetrieb empfundenen Beschleunigungen herankommen. Es hat sich gezeigt, dass der Immersionsgrad vor allem vom verwendeten Fahrzeugmodellen und den Motion-Cueing Algorithmus abhängig ist

    Algorithms and Applications for Nonlinear Model Predictive Control with Long Prediction Horizon

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    Fast implementations of NMPC are important when addressing real-time control of systems exhibiting features like fast dynamics, large dimension, and long prediction horizon, as in such situations the computational burden of the NMPC may limit the achievable control bandwidth. For that purpose, this thesis addresses both algorithms and applications. First, fast NMPC algorithms for controlling continuous-time dynamic systems using a long prediction horizon have been developed. A bridge between linear and nonlinear MPC is built using partial linearizations or sensitivity update. In order to update the sensitivities only when necessary, a Curvature-like measure of nonlinearity (CMoN) for dynamic systems has been introduced and applied to existing NMPC algorithms. Based on CMoN, intuitive and advanced updating logic have been developed for different numerical and control performance. Thus, the CMoN, together with the updating logic, formulates a partial sensitivity updating scheme for fast NMPC, named CMoN-RTI. Simulation examples are used to demonstrate the effectiveness and efficiency of CMoN-RTI. In addition, a rigorous analysis on the optimality and local convergence of CMoN-RTI is given and illustrated using numerical examples. Partial condensing algorithms have been developed when using the proposed partial sensitivity update scheme. The computational complexity has been reduced since part of the condensing information are exploited from previous sampling instants. A sensitivity updating logic together with partial condensing is proposed with a complexity linear in prediction length, leading to a speed up by a factor of ten. Partial matrix factorization algorithms are also proposed to exploit partial sensitivity update. By applying splitting methods to multi-stage problems, only part of the resulting KKT system need to be updated, which is computationally dominant in on-line optimization. Significant improvement has been proved by giving floating point operations (flops). Second, efficient implementations of NMPC have been achieved by developing a Matlab based package named MATMPC. MATMPC has two working modes: the one completely relies on Matlab and the other employs the MATLAB C language API. The advantages of MATMPC are that algorithms are easy to develop and debug thanks to Matlab, and libraries and toolboxes from Matlab can be directly used. When working in the second mode, the computational efficiency of MATMPC is comparable with those software using optimized code generation. Real-time implementations are achieved for a nine degree of freedom dynamic driving simulator and for multi-sensory motion cueing with active seat

    Preliminary guidelines for the rotorcraft certification by simulation process: update no. 1, March 2023

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    This document presents preliminary Guidance for the application of (rotorcraft) flight modelling and simulation in support of certification for compliance with standards CS-27 and CS-29, PART B (Flight) and other Flight related aspects (e.g. CS-29, Appendix B, Airworthiness Criteria for Helicopter Instrument Flight). The Guidance is presented in the form of a structured process, starting from the relevant paragraphs in the Certification Specifications, through a comprehensive description of the assembly of flight simulation requirements, informed by judgements on Influence, Predictability and Credibility, and on into the detailed building of the three major elements of the process: • the flight simulation model (FSM), • the flight simulator (FS), and • the flight test measurement system (FTMS). The FTMS feeds both the flight model and simulator development with real-world test data to support validation and fidelity assessment. A structured and systematic approach to data/configuration management and documentation is recommended, aided by the creation of the Rotorcraft Certification by Simulation (RCbS) project management plan. This is the first update of the RCbS Guidelines and includes modifications based on the first round of feedback received before and after the European Rotors RoCS workshop held in Cologne on November 9th 2022. The Guidelines will continue to be updated, as appropriate, with the next major revision to include exercising the process in case studies based on applicable certification requirements from EASA CS-27 and CS-29 (to appear in Section 10). In the current update, the RoCS team have also addressed the issue of resourcing the RCbS process (within Section 9) and suggested potential next steps for aspiring applicants (new Section 11)

    Subjective Evaluation of Vehicle Semi-Active Suspension for Improved Ride and Handling

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    The number of passenger cars currently equipped with semi-active suspensions has been steadily increasing in recent decades. These suspension systems provide an improvement in ride and handling when compared to passive suspensions. Currently, the approach to evaluating and tuning semi-active suspensions has been limited to objective methods or time-consuming alterations made on physical components. To alleviate the time and costs and improve the fidelity of such methods, a novel solution to subjectively evaluating vehicle semi-active suspensions is presented. The subjective evaluation method herein involves the use of a state-of-the-art dynamic driving simulator with drivers to subjectively evaluate and tune virtual semi-active suspensions. To consider the results of the proposed evaluation method accurate, high-fidelity vehicle models supplied by an OEM are studied. These vehicle models have previously been validated with objective and subjective performance data by an OEM’s expert drivers. First, offline co-simulations between VI-grade’s CarRealTime vehicle simulation software and several versions of a Simulink semi-active suspension controller are completed to objectively evaluate ride and handling. The semi-active suspension controller is based on several well-known control strategies and incorporates the vehicle’s passive suspension settings as one of the suspension modes. This feature permits a comparison between the passive and semi-active suspensions in terms of ride and handling. For the subjective evaluation, the vehicle and controller models are uploaded in a driver-in-the-loop environment. Expert drivers then execute a series of maneuvers and provide subjective feedback on the ride and handling of the different suspension modes. A questionnaire is implemented involving a list of subjective metrics tailored for ride and handling of semi-active suspensions. Furthermore, a correlation between changes in objective and subjective metrics is made to determine where correlation exists and to suggest predictive methods for future subjective ratings. A specific evaluation procedure is presented to ensure a bias among drivers is removed. The results of the subjective evaluation method prove that the method is effective at capturing relatively small changes in ride and handling, in a timely manner. The subjective ratings from the drivers showed acceptable agreement and considered many ride and handling improvements as major differences according to SAE standards. The correlation study identified a list of strong correlations between objective and subjective metrics. These results can be used to predict subjective performance when implementing offline changes to suspensions
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