VTechWorks Repository :: Browsing by Author "Sandu, Corina"

Browsing by Author "Sandu, Corina"

Now showing 1 - 20 of 162

Active Force Correction of Off-Nominal Structures Using Intelligent Scaffolding
Everson, Holly Kathleen (Virginia Tech, 2024-10-17)
The culmination of this research focuses on the area of structural support and stability as it relates to the field of large space structures. Fitting into the branch of in-space assembly, servicing, and manufacturing (ISAM), this topic covers essential subject matter areas of robotic manipulation, repair, state estimation, and structural health. As the next generation of space structures includes increased areas of modularity, the nature of structures built in-space lends itself significantly to repair efforts. With plans for these repair efforts in place, the lifetime of damaged structures can be greatly extended leading to a greater chance of mission success. By considering how repair efforts factor into the assembly scope, critical failures in large trusses, especially those involving single-point structural failures, can be mitigated. To do this, external forces are applied to the damaged structure utilizing an intelligent scaffolding formulation. This methodology employs robots to strategically apply loads to re-route abnormal stress and strain paths, correct for resulting deflections, and stabilize the structure itself. These tasks are vital to the safety of the structure and must take place before any repair efforts are considered in an effort to prevent cascading damage. The following research explores this damage simulation and correction paradigm through a variety of truss initial conditions, which allow for a suite of deflection responses. Utilizing these deflection responses a safe path for applying loads incrementally through generated waypoints is created with the help of the finite element modeler Ansys and a Python script. The ability for this system to successfully realign the wide scope of truss cases showcases that it is a truly adaptive system. Although this work is primarily proven within a simulation space, efforts to contextualize in a physical system and explore the elements needed to implement this method are also described. Finally, although this research is presented within the scope of damage repair, the final chapter looks to apply this method to other similarly unsupported structures by examining how critical it can be during assembly scenarios.
Active Suspension Design Requirements for Compliant Boundary Condition Road Disturbances
Srinivasan, Anirudh (Virginia Tech, 2017-09-05)
The aim of suspension systems in vehicles is to provide the best balance between ride and handling depending on the operating conditions of a vehicle. Active suspensions are far more effective over a variety of different road conditions compared to passive suspension systems. This is because of their ability to store and dissipate energy at different rates. Additionally, they can even provide energy of their own into the rest of the system. This makes active suspension systems an important topic of research in suspension systems. The biggest benefit of having an active suspension system is to be able to provide energy into the system that can minimize the response of the sprung mass. This is done using actuators. Actuator design in vehicle suspension system is an important research topic and a lot of work has been done in the field but little work has been done to estimate the peak control force and bandwidth required to minimize the response of the sprung mass. These two are very important requirements for actuator design in active suspensions. The aim of this study is estimate the peak control force and bandwidth to minimize the acceleration of the sprung mass of a vehicle while it is moving on a compliant surface. This makes the road surface a bi-lateral boundary and hence, the total system is a combination of the vehicle and the compliant road. Generalized vehicle and compliant road models are created so that parameters can be easily changed for different types of vehicles and different road conditions. The peak control force is estimated using adaptive filtering. A least mean squares (LMS) algorithm is used in the process. A case study with fixed parameters is used to show the results of the estimation process. The results show the effectiveness of an adaptive LMS algorithm for such an application. The peak control force and the bandwidth that are obtained from this process can then be used in actuator design.
Adaptive control of a DDMR with a Robotic Arm
Chaure, Rishabh Subhash (Virginia Tech, 2021-11-30)
Robotic arms are essential in a variety of industrial processes. However, the dexterous workspace of a robotic arm is limited. This limitation can be overcome by making the robotic arm mobile. Such robots, which comprise a robotic manipulator installed on a wheeled mobile platform, are called mobile robots. A mobile manipulator can attain a position in space which a robotic arm with fixed base may not be able to reach otherwise. To be applicable to a variety of scenarios, these robots need to meet user-defined margins on their trajectory tracking error, irrespective of the payload transported, faults, and failures. In this thesis, we study the dynamics of mobile manipulator comprising both a differential-drive mobile robot (DDMR) and a robotic arm. Thus, we design a model reference adaptive controller (MRAC) for this mobile manipulator to regulate this vehicle and guarantee robustness to uncertainties in the robot's inertial properties such as the mass of the payload transported and friction coefficients.
Advanced Multibody Dynamics Modeling of the Freight Train Truck System
Ballew, Brent Steven (Virginia Tech, 2008-04-28)
Previous work in the Railway Technology Laboratory at Virginia Tech focused on better capturing the dynamics of the friction wedge, modeled as a 3D rigid body. The current study extends that work to a half-truck model treated as an application of multibody dynamics with unilateral contact to model the friction wedge interactions with the bolster and the sideframe. The half-truck model created in MATLAB is a 3D, dynamic, multibody dynamics model comprised of four rigid bodies: a bolster, two friction wedges, and a sideframe assembly. The model allows each wedge four degrees of freedom: vertical displacement, longitudinal displacement (between the bolster and sideframe), pitch (rotation around the lateral axis), and yaw (rotation around the vertical axis). The bolster and the sideframe have only the vertical degree of freedom. The geometry of these bodies can be adjusted for various simulation scenarios. The bolster can be initialized with a pre-defined yaw (rotation around the vertical axis) and the sideframe may be initialized with a pre-defined pitch/toe (rotation around the lateral axis). The multibody dynamics half-truck model simulation results have been compared with results from NUCARS®, an industry standard train modeling software, for similar inputs. The multibody dynamics models have also been extended to a variably damped full-truck model and a variably damped half-truck warping model. These models were reformulated to react dynamically to simulated truck warp inputs. The ability to better characterize truck warping properties can prevent train roll over and derailments from truck hunting. In a quarter-truck variably damped configuration the effects of a curved wedge surface has also been explored. Actual friction wedges have surfaces which are slightly curved, this iteration in the multibody dynamics friction wedge modeling attempts to draw one step closer to actual friction wedge geometry. This model lays the ground work for a contact dependant wedge wearing model based on material properties and tribology.
Affordable Haptic Gloves Beyond the Fingertips
Ahn, Suyeon (Virginia Tech, 2023-10-11)
With the increase in popularity of virtual reality (VR) systems, haptic devices have been garnering interest as means of augmenting users' immersion and experiences in VR. Unfortunately, most commercial gloves available on the market are targeted towards enterprise and research, and are too expensive to be accessible to the average consumer for entertainment. Some efforts have been made by gaming and do-it-yourself (DIY) enthusiasts to develop cheap, accessible haptic gloves, but due to cost limitations, the designs are often simple and only provide feedback at the fingertips. Considering the many types of grasps used by humans to interact with objects, it is evident that haptic gloves must offer feedback to many regions of the hand, such as the palm and lengths of the fingers to provide more realistic feedback. This thesis discusses a novel, affordable design that provides haptic feedback to the intermediate and proximal phalanges of the fingers (index, middle, ring and pinkie) using a ratchet and pawl actuation mechanism.
Analysis and Development of Control Methodologies for Semi-active Suspensions
Ghasemalizadeh, Omid (Virginia Tech, 2016-11-14)
Semi-active suspensions have drawn particular attention due to their superior performance over the other types of suspensions. One of their advantages is that their damping coefficient can be controlled without the need for any external source of power. In this study, a handful of control approaches are implemented on a car models using MATLAB/Simulink. The investigated control methodologies are skyhook, groundhook, hybrid skyhook-groundhook, Acceleration Driven Damper, Power Driven Damper, H∞ Robust Control, Fuzzy Logic Controller, and Inverse ANFIS. H∞ Robust Control is an advanced method that guarantees transient performance and rejects external disturbances. It is shown that H∞ with the proposed modification, has the best performance although its relatively high cost of computation could be potentially considered as a drawback. Also, the proposed Inverse ANFIS controller uses the power of fuzzy systems along with neural networks to help improve vehicle ride metrics significantly. In this study, a novel approach is introduced to analyze and fine-tune semi-active suspension control algorithms. In some cases, such as military trucks moving on off-road terrains, it is critical to keep the vehicle ride quality in an acceptable range. Semi-active suspensions are used to have more control over the ride metrics compared to passive suspensions and also, be more cost-effective compared to active suspensions. The proposed methodology will investigate the skyhook-groundhook hybrid controller. This is accomplished by conducting sensitivity analysis of the controller performance to varying vehicle/road parameters. This approach utilizes sensitivity analysis and one-at-a-time methodology to find and reach the optimum point of vehicle suspensions. Furthermore, real-time tuning of the mentioned controller will be studied. The online tuning will help keep the ride quality of the vehicle close to its optimum point while the vehicle parameters are changing. A quarter-car model is used for all simulations and analyses.
Analytical Evaluation of the Accuracy of Roller Rig Data for Studying Creepage in Rail Vehicles
Keylin, Alexander (Virginia Tech, 2013-01-23)
The primary purpose of this research is to investigate the effectiveness of a scaled roller rig for accurately assessing the contact mechanics and dynamics between a profiled steel wheel and rail, as is commonly used in rail vehicles. The established creep models of Kalker and Johnson and Vermeulen are used to establish correction factors, scaling factors, and transformation factors that allow us to relate the results from a scaled rig to those of a tangent track. ï¿½Correction factors, which are defined as the ratios of a given quantity (such as creep coefficient) between a roller rig and a track, are derived and used to relate the results between a full-size rig and a full-size track. Scaling factors are derived to relate the same quantities between roller rigs of different scales. Finally, transformation factors are derived by combining scaling factors with correction factors in order to relate the results from a scaled roller rig to a full-size tangent track. Close-end formulae for creep force correction, scaling, and transformation factors are provided in the thesis, along with their full derivation and an explanation of their limitations; these formulae can be used to calculate the correction factors for any wheel-rail geometry and scaling. For Kalker's theory, it is shown that the correction factor for creep coefficients is strictly a function of wheel and rail geometry, primarily the wheel and roller diameter ratio. For Johnson and Vermeulen's theory, the effects of creepage, scale, and load on the creep force correction factor are demonstrated. ï¿½It is shown that INRETS' scaling strategy causes the normalized creep curve to be identical for both a full-size and a scaled roller rig. ï¿½It is also shown that the creep force correction factors for Johnson and Vermeulen's model increase linearly with creepage, starting with the values predicted by Kalker's theory. ï¿½Therefore, Kalker's theory provides a conservative estimate for creep force correction factors. ï¿½A case study is presented to demonstrate the creep curves, as well as the correction and transformation factors, for a typical wheel-rail configuration. ï¿½Additionally, two studies by other authors that calculate the correction factor for Kalker's creep coefficients for specific wheel-rail geometries are reviewed and show full agreement with the results that are predicted by the formulae derived in this study. ï¿½Based on a review of existing and past roller rigs, as well as the findings of this thesis, a number of recommendations are given for the design of a roller rig for the purpose of assessing the wheel-rail contact mechanics. ï¿½A scaling strategy (INRETS') is suggested, and equations for power consumption of a roller rig are derived. Recommendations for sensors and actuators necessary for such a rig are also given. Special attention is given to the resolution and accuracy of velocity sensors, which are required to properly measure and plot the creep curves.
Analytical Modeling for Sliding Friction of Rubber-Road Contact
Vadakkeveetil, Sunish (Virginia Tech, 2017-04-21)
Rubber friction is an important aspect to tire engineers, material developers and pavement engineers because of its importance in the estimation of forces generated at the contact, which further helps in optimizing tire and vehicle performances, and to estimate tire wear. It mainly depends on the material properties, contact mechanics and operating condition. There are two major contributions to rubber friction, due to repeated viscoelastic deformation from undulations of surface called hysteresis and due to Vander Waals interaction of the molecules called adhesion. The study focuses on analytical modeling of friction for stationary sliding of rubber block on rough surfaces. Two novel approaches are discussed and compared. Frictional shear stress is obtained from the energy dissipated at the contact interface due to the elastic deformations of rubber block at different length scales. Contact mechanics theories based on continuity approach combined with stochastic processes to estimate the real contact area, mean penetration depth and true stresses at contact depending on operating conditions. Rubber properties are highly temperature dependent. Temperature model developed based on heat diffusion relation is integrated to consider the effects of temperature rise due to frictional heating. Model results are validated with theoretical results of literature. Simulation results of friction model is obtained for Compound A sliding on rough surface. Material properties are obtained using Dynamic Mechanical Analysis and Time temperature superposition. Influence of the friction models under different conditions are discussed. Model results are validated with experimental data from Dynamic friction tester on a 120-grit surface followed by future works.
Anthropomimetic Control Synthesis: Adaptive Vehicle Traction Control
Kirchner, William (Virginia Tech, 2012-03-22)
Human expert drivers have the unique ability to build complex perceptive models using correlated sensory inputs and outputs. In the case of longitudinal vehicle traction, this work will show a direct correlation in longitudinal acceleration to throttle input in a controlled laboratory environment. In fact, human experts have the ability to control a vehicle at or near the performance limits, with respect to vehicle traction, without direct knowledge of the vehicle states; speed, slip or tractive force. Traditional algorithms such as PID, full state feedback, and even sliding mode control have been very successful at handling low level tasks where the physics of the dynamic system are known and stationary. The ability to learn and adapt to changing environmental conditions, as well as develop perceptive models based on stimulus-response data, provides expert human drivers with significant advantages. When it comes to bandwidth, accuracy, and repeatability, automatic control systems have clear advantages over humans; however, most high performance control systems lack many of the unique abilities of a human expert. The underlying motivation for this work is that there are advantages to framing the traction control problem in a manner that more closely resembles how a human expert drives a vehicle. The fundamental idea is the belief that humans have a unique ability to adapt to uncertain environments that are both temporal and spatially varying. In this work, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy. The proposed anthropomimetic traction control algorithm operates on the same correlated input signals that a human expert driver would in order to maximize traction. A gradient ascent approach is at the heart of the proposed anthropomimetic control algorithm, and a real-time implementation is described using linear operator techniques, even though the tire-ground interface is highly non-linear. Performance of the proposed anthropomimetic traction control algorithm is demonstrated using both a longitudinal traction case study and a combined mode traction case study, in which longitudinal and lateral accelerations are maximized simultaneously. The approach presented in this research should be considered as a first step in the development of a truly anthropomimetic solution, where an advanced control algorithm has been designed to be responsive to the same limited input signals that a human expert would rely on, with the objective of maximizing traction. This work establishes the foundation for a general framework for an anthropomimetic control algorithm that is capable of learning and adapting to an uncertain, time varying environment. The algorithms developed in this work are well suited for efficient real time control in ground vehicles in a variety of applications from a driver assist technology to fully autonomous applications.
Application of Multifunctional Doppler LIDAR for Non-contact Track Speed, Distance, and Curvature Assessment
Munoz, Joshua (Virginia Tech, 2015-12-08)
The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheel-mounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to high-fidelity distance and curvature data through utilization of processor clock rate and left-and right-rail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a 'Hy-Rail' utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in various weather conditions, providing high-accuracy data to further calculate distance and curvature along the test routes. Tests results indicate the LIDAR system measures speed at higher accuracy than the encoder, absent of noise influenced by increasing speed. Distance calculation is also high in accuracy, results showing high correlation with encoder and ground truth data. Finally, curvature calculation using speed data is shown to have good correlation with IMU measurements and a resolution capable of revealing localized track alignments. Further investigations involve a curve measurement algorithm and speed calibration method independent from external reference systems, namely encoder and ground truth data. The speed calibration results show a high correlation with speed data from the track geometry vehicle. It is recommended that the study be extended to provide assessment of the LIDAR's sensitivity to car body motion in order to better isolate the embedded behavior in the speed and curvature profiles. Furthermore, in the interest of progressing the system toward a commercially viable unit, methods for self-calibration and pre-processing to allow for fully independent operation is highly encouraged.
Artificial Neural Networks based Modeling and Analysis of Semi-Active Damper System
Bhanot, Nishant (Virginia Tech, 2017-06-30)
The suspension system is one of the most sensitive systems of a vehicle as it affects the dynamic behavior of the vehicle with even minor changes. These systems are designed to carry out multiple tasks such as isolating the vehicle body from the road/tire vibrations as well as achieving desired ride and handling performance levels in both steady state and limit handling conditions. The damping coefficient of the damper plays a crucial role in determining the overall frequency response of the suspension system. Considerable research has been carried out on semi active damper systems as the damping coefficient can be varied without the system requiring significant external power giving them advantages over both passive and fully active suspension systems. Dampers behave as non-linear systems at higher frequencies and hence it has been difficult to develop accurate models for its full range of motion. This study aims to develop a velocity sensitive damper model using artificial neural networks and essentially provide a 'black-box' model which encapsulates the non-linear behavior of the damper. A feed-forward neural network was developed by testing a semi active damper on a shock dynamometer at CenTiRe for multiple frequencies and damping ratios. This data was used for supervised training of the network using MATLAB Neural Network Toolbox. The developed NN model was evaluated for its prediction accuracy. Further, the developed damper model was analyzed for feasibility of use for simulations and controls by integrating it in a Simulink based quarter car model and applying the well-known skyhook control strategy. Finally, effects on ride and handling dynamics were evaluated in Carsim by replacing the default damper model with the proposed model. It was established that this damper modeling technique can be used to help evaluate the behavior of the damper on both component as well as vehicle level without needing to develop a complex physics based model. This can be especially beneficial in the earlier stages of vehicle development.
Asymmetric Energy Harvesting and Hydraulically Interconnected Suspension: Modeling and Validations
Chen, YuZhe (Virginia Tech, 2020-11-30)
Traditional vehicle suspension system is equipped with isolated shock absorbers that can only dissipate energy by themselves. Hydraulic interconnected suspension uses hydraulic circuits to connect each shock absorber, so that the energized hydraulic fluid can be utilized to counter unwanted body motion to improve the overall dynamic performance. The hydraulic interconnected suspension is a proven concept that has shown good potential in controlling body rolling and decoupling the warp mode from other dynamic modes. Hydraulic interconnected suspension is still passive and lack of adaptivity, while some active or semi-active suspension technologies allow the shock absorbers to counter the road disturbances using external power input. Active suspensions such as electro-magnetic shock absorbers use the variable viscosity of magnetofluid to alter the damping characteristics of the suspension to adapt to quickly changing road conditions. The energy demand from an active suspension can reach the level of kilowatts in certain cases, which results in lowered fuel efficiency of the vehicle. To find a balanced solution to dynamic performance and energy efficiency, this paper introduces a new form of energy-harvesting suspension that is integrated in a hydraulically interconnected suspension (HIS) system. The combined energy-harvesting and hydraulic interconnection features provide improved energy efficiency and vehicle dynamics performance. A single cylinder model is built in AMESim for preliminary study and validated in a bench test. The bench test results proved the authenticity of the theoretical model, and the model is then used to predict the system performance and guide the hardware construction. Based on the proven single cylinder model, and a full car model are developed to validate the effectiveness of the overall system design. Different dynamic input scenarios are used for model simulation, which includes single-wheel sinusoidal input, braking test and double lane change test. In the double lane change test, the EHHIS sees averagely 70% improved in roll angle relative to a conventional suspension, and averagely 22% improvement relative to simple hydraulically interconnected suspension. The power generated is found to reach maximum at 4 Ω external resistance and the highest average power generated is more than 70 watts at 2 hz 20 mm sinusoidal input. A road test of a half vehicle EHHIS system is done. From the road test results, the EHHIS meets the expectations of reducing roll angles. The riding comfort is evaluated with the RMS value of the vertical acceleration and is found to have minimum compromise from the greater damping coefficient.
Autonomous Cricothyroid Membrane Detection and Manipulation using Neural Networks and Robot Arm for First-Aid Airway Management
Han, Xiaoxue (Virginia Tech, 2020-06-02)
The thesis focuses on applying deep learning and reinforcement learning techniques on human keypoint detection and robot arm manipulation. Inspired by Semi-Autonomous Victim Extraction Robot (SAVER), an autonomous first-aid airway-management robotic system designed to perform Cricothyrotomy on patients is proposed. Perception, decision-making, and control are embedded in the system. In this system, first, the location of the cricothyroid membrane (CTM)-the incision site of Cricothyrotomy- is detected; then, the robot arm is controlled to reach the detected position on a medical manikin. A hybrid neural network (HNNet) that can balance both speed and accuracy is proposed. HNNet is an ensemble-based network architecture that consists of two ensembles: the region proposal ensemble and the keypoint detection ensemble. This architecture can maintain the original high resolution of the input image without heavy computation and can meet the high-precision and real-time requirements at the same time. A dataset containing more than 16,000 images from 13 people, with a clear view of the neck area, and with CTM position labeled by a medical expert was built to train and validate the proposed model. It achieved a success rate of $99.6%$ to detect the position of the CTM with an error of less than 5mm. The robot arm manipulator was trained with the reinforcement learning model to reach the detected location. Finally, the detection neural network and the manipulation process are combined as an integrated system. The system was validated in real-life experiments on a human-sized medical manikin using a Kinect V2 camera and a MICO robot arm manipulator.
Autonomous Sample Collection Using Image-Based 3D Reconstructions
Torok, Matthew M. (Virginia Tech, 2012-04-26)
Sample collection is a common task for mobile robots and there are a variety of manipulators available to perform this operation. This thesis presents a novel scoop sample collection system design which is able to both collect and contain a sample using the same hardware. To ease the operator burden during sampling the scoop system is paired with new semi-autonomous and fully autonomous collection techniques. These are derived from data provided by colored 3D point clouds produced via image-based 3D reconstructions. A custom robotic mobility platform, the Scoopbot, is introduced to perform completely automated imaging of the sampling area and also to pick up the desired sample. The Scoopbot is wirelessly controlled by a base station computer which runs software to create and analyze the 3D point cloud models. Relevant sample parameters, such as dimensions and volume, are calculated from the reconstruction and reported to the operator. During tests of the system in full (48 images) and fast (6-8 images) modes the Scoopbot was able to identify and retrieve a sample without any human intervention. Finally, a new building crack detection algorithm (CDA) is created to use the 3D point cloud outputs from image sets gathered by a mobile robot. The CDA was shown to successfully identify and color-code several cracks in a full-scale concrete building element.
Biomechanical Assessment and Metabolic Evaluation of Passive Lift-Assistive Exoskeletons During Repetitive Lifting Tasks
Alemi, Mohammad Mehdi (Virginia Tech, 2019-09-16)
Work-related musculoskeletal disorders (WMSDs) due to overexertion and consequently the low back pain (LBP) are one of the most prevalent sources of nonfatal occupational injuries and illnesses in all over the world. In the past several years, the industrial exoskeletons especially the passive ones have been proposed as alternative intervention and assistive devices, which are capable of reducing the risk of WMSDs and LBP. However, more research is warranted to validate the applicability of these exoskeletons. In addition, because the majority of previous studies have been limited to specific lifting tasks using only one type of lift assistive exoskeleton, more research is needed to examine the effect of alteration of different lift-assistive exoskeletons on reducing the activity of back muscles and metabolic reduction. The main objective of this dissertation is to render an overview of three studies that attempt to improve the literature by providing comprehensive biomechanical evaluations and metabolic assessments of three passive lift-assistive exoskeletons (VT-Lowe's Exoskeleton (developed in ARLab at VT), Laevo and SuitX). This dissertation has been composed of three related studies. The first study aimed to investigate and examine the capability of a novel lift assistive exoskeleton, VT-Lowe's exoskeleton, in reducing the peak and mean activity of back and leg muscles. Findings revealed that the exoskeleton significantly decreased the peak and mean activity of back muscles (IL(iliocostalis lumborum) and LT(longissimus thoracis)) by 31.5% and 29.3% respectively for symmetric lifts, and by 28.2% and 29.5% respectively for asymmetric lifts. Furthermore, the peak and mean EMG of leg muscles were significantly reduced by 19.1% and 14.1% during symmetric lifts, and 17.4% and 14.6% during asymmetric lifts. Interestingly, the VT-Lowe's exoskeleton showed higher reduction in activity of back and leg muscles compared to other passive lift-assistive exoskeletons available in the literatures. In the second study, the metabolic cost reduction associated with the use of VT-Lowe's exoskeleton during freestyle lifting was theoretically modelled, validated and corresponding metabolic savings were reported. The metabolic cost and the oxygen consumption results supported the hypothesis that the VT-Lowe's exoskeleton could significantly reduce the metabolic demands (~7.9% on average) and oxygen uptake (~8.7% on average) during freestyle lifting. Additionally, we presented a prediction model for the metabolic cost of exoskeleton during repetitive freestyle lifting tasks. The prediction models were very accurate as the absolute prediction errors were small for both 0% (< 1.4%) and 20% (< 0.7%) of body weight. In the third study, the biomechanical evaluation, energy expenditure and subjective assessments of two passive back-support exoskeletons (Laevo and SuitX) were examined in the context of repetitive lifting tasks. The experimental lifting tasks in this study were simulated in a laboratory environment for two different levels of lifting symmetry (symmetric vs. asymmetric) and lifting posture (standing vs. kneeling). Results of this study demonstrated that using both exoskeletons during dynamic lifting tasks could significantly lower the peak activity of trunk extensor muscles by ~10-28%. In addition, using both exoskeletons could save the energy expenditure by ~4-13% in all conditions tested by partially offsetting the weight of the torso. Such reductions were, though, task-dependent and differed between the two tested exoskeletons. Overall, the results of all three studies in this dissertation showed the capability of passive lift-assistive exoskeletons in reducing the activity of back and leg muscles and providing metabolic savings during repetitive lifting tasks.
Characterization of Soft Clay and Clay-tire Interaction for the Prediction of Ground Mobility
Pandit, Rashna (Virginia Tech, 2023-08-22)
Predicting tire performance on soft, fine-grained soils is required for many off-road explorations in the military, mining, agricultural, and earth-moving sectors. However, the mobility in deformable material is extremely challenging, especially in the presence of water. Although there is a significant amount of research on terrains such as sands, there is a lack of research on fine-grained soils. This research is part of a bigger project that presents a novel approach to improve the mobility of off-road vehicles on wet deformable soils. The approach integrates experimental data from small-scale soil testing, large-scale soil-tire interaction testing, and advanced physics-based numerical simulation techniques. In particular, this thesis attempts to characterize the clay-tire interface by conducting large-scale direct shear tests. In addition to clay-tire contact friction, the properties and strength parameters of the soft clay are determined by conducting various index properties and advanced tests. The testing program accounts for different stresses, loading conditions, and boundary conditions, decided taking into account real field conditions. The results from all these experiments will be used to calibrate and validate the material constitutive models required for the development of a mobility predictive numerical model. Overall, this study contributes to the development of more advanced and accurate terramechanics models that involve deformable terrains like soft clays.
Collaborative Locomotion of Quadrupedal Robots: From Centralized Predictive Control to Distributed Control
Kim, Jeeseop (Virginia Tech, 2022-08-26)
This dissertation aims to realize the goal of deploying legged robots that cooperatively walk to transport objects in complex environments. More than half of the Earth's continent is unreachable to wheeled vehicles---this motivates the deployment of collaborative legged robots to enable the accessibility of these environments and thus bring robots into the real world. Although significant theoretical and technological advances have allowed the development of distributed controllers for complex robot systems, existing approaches are tailored to the modeling and control of multi-agent systems composed of collaborative robotic arms, multi-fingered robot hands, aerial vehicles, and ground vehicles, but not collaborative legged agents. Legged robots are inherently unstable, unlike most of the systems where these algorithms have been deployed. Models of cooperative legged robots are further described by high-dimensional, underactuated, and complex hybrid dynamical systems, which complicate the design of control algorithms for coordination and motion control. There is a fundamental gap in knowledge of control algorithms for safe motion control of these inherently unstable hybrid dynamical systems, especially in the context of collaborative work. The overarching goal of this dissertation is to create a formal foundation based on scalable optimization and robust and nonlinear control to develop distributed and hierarchical feedback control algorithms for cooperative legged robots to transport objects in complex environments. We first develop a hierarchical nonlinear control algorithm, based on model predictive control (MPC), quadratic programming (QP), and virtual constraints, to generate and stabilize locomotion patterns in a real-time manner for dynamical models of single-agent quadrupedal robots. The higher level of the proposed control scheme is developed based on an event-based MPC that computes the optimal center of mass (COM) trajectories for a reduced-order linear inverted pendulum (LIP) model subject to the feasibility of the net ground reaction force (GRF). QP-based virtual constraint controllers are developed at the lower level of the proposed control scheme to impose the full-order dynamics to track the optimal trajectories while having all individual GRFs in the friction cone. The analytical results are numerically verified to demonstrate stable and robust locomotion of a 22 degree of freedom (DOF) quadrupedal robot, in the presence of payloads, external disturbances, and ground height variations. We then present a hierarchical nonlinear control algorithm for the real-time planning and control of cooperative locomotion of legged robots that collaboratively carry objects. An innovative network of reduced-order models subject to holonomic constraints, referred to as interconnected LIP dynamics, is presented to study quasi-statically stable cooperative locomotion. The higher level of the proposed algorithm employs a supervisory controller, based on event-based MPC, to effectively compute the optimal reduced-order trajectories for the interconnected LIP dynamics. The lower level of the proposed algorithm employs distributed nonlinear controllers to reduce the gap between reduced- and full-order complex models of cooperative locomotion. We numerically investigate the effectiveness of the proposed control algorithm via full-order simulations of a team of collaborative quadrupedal robots, each with a total of 22 DOFs. The dissertation also investigates the robustness of the proposed control algorithm against uncertainties in the payload mass and changes in the ground height profile. Finally, we present a layered control approach for real-time trajectory planning and control of dynamically stable cooperative locomotion by two holonomically constrained quadrupedal robots. An innovative and interconnected network of reduced-order models, based on the single rigid body (SRB) dynamics, is developed for trajectory planning purposes. At the higher level of the control scheme, two different MPC algorithms are proposed to address the optimal control problem of the interconnected SRB dynamics: centralized and distributed MPCs. The MPCs compute the reduced-order states, GRFs, and interaction wrenches between the agents. The distributed MPC assumes two local QPs that share their optimal solutions according to a one-step communication delay and an agreement protocol. At the lower level of the control scheme, distributed nonlinear controllers are employed to impose the full-order dynamics to track the prescribed and optimal reduced-order trajectories and GRFs. The effectiveness of the proposed layered control approach is verified with extensive numerical simulations and experiments for the blind, robust, and cooperative locomotion of two holonomically constrained A1 robots with different payloads on different terrains and in the presence of external disturbances. It is shown that the distributed MPC has a performance similar to that of the centralized MPC, while the computation time is reduced significantly.
Compacted Snow Testing Methodology and Instrumentation
Shenvi, Mohit Nitin (Virginia Tech, 2024-03-05)
Snow is a complex material that is difficult to characterize especially due to its high compressibility and temperature-sensitive nonlinear viscoelasticity. Snow mechanics has been intensively investigated by avalanche and army researchers for decades. However, fewer research studies have been published for compacted snow, commonly defined as snow with a density in the range of 370-560 kg/m3. From a mobility perspective, the tires are the primary point of force and motion generation and their interaction with the terrain causes an increased reliance on the skill of the driver for safer mobility. Thus, standards like ASTM F1805 are implemented for the evaluation of winter tires which can be used in harsh conditions like ice and snow. This work focuses on evaluating the prior efforts performed for the measurement of snow properties. In addition, analysis using regression models and principal component analysis is performed to understand the extent to which specific measurements related to snow affect the traction of the tire. It was found that the compressive and shear properties of snow contribute more than 90% to the variation in the traction coefficient of a tire when evaluated on a compacted snow domain per ASTM F1805. Identification of this phenomenon allowed the enhancement of an existing device that can be used for measuring the compaction and shear properties of snow. The device hence conceptualized was manufactured in-house and tested at the Smithers Winter Test Center to benchmark against existing devices available commercially. Further, a more analytical method for evaluating the resistive pressure for the penetration of the device was formulated. Based on this, a possible framework for the determination of the bevameter parameters using measurements of the new device has been proposed which needs to be validated experimentally and computationally.
Comparative Analysis of Lightweight Robotic Wheeled and Tracked Vehicle
Johnson, Christopher Patrick (Virginia Tech, 2012-04-26)
This study focuses on conducting a benchmarking analysis for light wheeled and tracked robotic vehicles. Vehicle mobility has long been a key aspect of research for many organizations. According to the Department of Defense vehicle mobility is defined as, "the overall capacity to move from place to place while retaining its ability to perform its primary mission"[1]. Until recently this definition has been applied exclusively to large scale wheeled and tracked vehicles. With new development lightweight ground vehicles designed for military and space exploration applications, the meaning of vehicle mobility must be revised and the tools at our disposal for evaluating mobility must also be expanded. In this context a significant gap in research is present and the main goal of this thesis is to help fill the void in knowledge regarding small robotic vehicle mobility assessment. Another important aspect of any vehicle is energy efficiency. Thus, another aim of this study is to compare the energy needs for a wheeled versus tracked robot, while performing similar tasks. The first stage of the research is a comprehensive review of the state-of-the-art in vehicle mobility assessment. From this review, a mobility assessment criterion for light robots will be developed. The second stage will be outfitting a light robotic vehicle with a sensor suite capable of capturing relevant mobility criteria. The third stage of this study will be an experimental investigation of the mobility capability of the vehicle. Finally the fourth stage will include quantitative and qualitative evaluation of the benchmarking study.
Comparative Study of the Effect of Tread Rubber Compound on Tire Performance on Ice
Shenvi, Mohit Nitin (Virginia Tech, 2020-08-20)
The tire-terrain interaction is complex and tremendously important; it impacts the performance and safety of the vehicle and its occupants. Icy roads further enhance these complexities and adversely affect the handling of the vehicle. The analysis of the tire-ice contact focusing on individual aspects of tire construction and operation is imperative for tire industry's future. This study investigates the effects of the tread rubber compound on the drawbar pull performance of tires in contact with an ice layer near its melting point. A set of sixteen tires of eight different rubber compounds were considered. The tires were identical in design and tread patterns but have different tread rubber compounds. To study the effect of the tread rubber compound, all operational parameters were kept constant during the testing conducted on the Terramechanics Rig at the Terramechanics, Multibody, and Vehicle Systems laboratory. The tests led to conclusive evidence of the effect of the tread rubber compound on the drawbar performance (found to be most prominent in the linear region of the drawbar-slip curve) and on the resistive forces of free-rolling tires. Modeling of the tire-ice contact for estimation of temperature rise and water film height was performed using ATIIM 2.0. The performance of this in-house model was compared against three classical tire-ice friction models. A parametrization of the Magic Formula tire model was performed using experimental data and a Genetic Algorithm. The dependence of individual factors of the Magic Formula on the ambient temperature, tire age, and tread rubber compounds was investigated.

Browsing by Author "Sandu, Corina"

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