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- Genre: Masters Thesis
- Creators: Berman, Spring
Description
This thesis is a qualitative research study that focuses on siblings of children with Autistic Spectrum Disorder (ASD). Even though it is expected that having a child with ASD in the family will influence the whole family including siblings of the child with ASD, the sibling population is rarely included in research related to children with ASD, and there is only limited services available for them. This exploratory study (n=6) is aimed at better understanding the siblings' lives in their family settings in order to identify the siblings' unmet needs and determine how they have been influenced by the child with ASD. This study is also aimed at identifying the most appropriate support for the siblings to help them cope better. The study followed the Resiliency Model of Family Stress, Adjustment, and Adaptation and a narrative theory approach. An in-depth interview with the parents was conducted for the study, so the findings reflect the parents' perception of the siblings. All the themes emerged into two categories: life in the family setting and supports. The findings indicate that the families are striving for balance between the siblings and the children with ASD, but still tend to focus more on the children with ASD. Also, the families tend to have autonomous personal support systems. The parents tend to perceive that these personal support systems are good enough for the siblings; therefore, the parents do not feel that formal support for the siblings was necessary. As a result of the findings, recommendations are made for the organizations that work with individuals with ASD to provide more appropriate services for the families of children with ASD, including siblings. Also, recommendations are made for future studies to clarify more factors related to the siblings due to the limitation of this study; the siblings' lives were reflected vicariously via the parents.
ContributorsJeong, Seong Hae (Author) / Marsiglia, Flavio F (Thesis advisor) / Ayers, Stephanie (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2013
Description
The presented work in this report is about Real time Estimation of wind and analyzing current wind correction algorithm in commercial off the shelf Autopilot board. The open source ArduPilot Mega 2.5 (APM 2.5) board manufactured by 3D Robotics is used. Currently there is lot of development being done in the field of Unmanned Aerial Systems (UAVs), various aerial platforms and corresponding; autonomous systems for them. This technology has advanced to such a stage that UAVs can be used for specific designed missions and deployed with reliability. But in some areas like missions requiring high maneuverability with greater efficiency is still under research area. This would help in increasing reliability and augmenting range of UAVs significantly. One of the problems addressed through this thesis work is, current autopilot systems have algorithm that handles wind by attitude correction with appropriate Crab angle. But the real time wind vector (direction) and its calculated velocity is based on geometrical and algebraic transformation between ground speed and air speed vectors. This method of wind estimation and prediction, many a times leads to inaccuracy in attitude correction. The same has been proved in the following report with simulation and actual field testing. In later part, new ways to tackle while flying windy conditions have been proposed.
ContributorsBiradar, Anandrao Shesherao (Author) / Saripalli, Srikanth (Thesis advisor) / Berman, Spring (Thesis advisor) / Thanga, Jekan (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis focuses on the theoretical work done to determine thermodynamic properties of a chalcopyrite thin-film material for use as a photovoltaic material in a tandem device. The material of main focus here is ZnGeAs2, which was chosen for the relative abundance of constituents, favorable photovoltaic properties, and good lattice matching with ZnSnP2, the other component in this tandem device. This work is divided into two main chapters, which will cover: calculations and method to determine the formation energy and abundance of native point defects, and a model to calculate the vapor pressure over a ternary material from first-principles. The purpose of this work is to guide experimental work being done in tandem to synthesize ZnGeAs2 in thin-film form with high enough quality such that it can be used as a photovoltaic. Since properties of photovoltaic depend greatly on defect concentrations and film quality, a theoretical understanding of how laboratory conditions affect these properties is very valuable. The work done here is from first-principles and utilizes density functional theory using the local density approximation. Results from the native point defect study show that the zinc vacancy (VZn) and the germanium antisite (GeZn) are the more prominent defects; which most likely produce non-stoichiometric films. The vapor pressure model for a ternary system is validated using known vapor pressure for monatomic and binary test systems. With a valid ternary system vapor pressure model, results show there is a kinetic barrier to decomposition for ZnGeAs2.
ContributorsTucker, Jon R (Author) / Van Schilfgaarde, Mark (Thesis advisor) / Newman, Nathan (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2011
Description
As world energy demands increase, research into more efficient energy production methods has become imperative. Heterogeneous catalysis and nanoscience are used to promote chemical transformations important for energy production. These concepts are important in solid oxide fuel cells (SOFCs) which have attracted attention because of their potential to provide an efficient and environmentally favorable power generation system. The SOFC is also fuel-flexible with the ability to run directly on many fuels other than hydrogen. Internal fuel reforming directly in the anode of the SOFC would greatly reduce the cost and complexity of the device. Methane is the simplest hydrocarbon and a main component in natural gas, making it useful when testing catalysts on the laboratory scale. Nickel (Ni) and gadolinium (Gd) doped ceria (CeO2) catalysts for potential use in the SOFC anode were synthesized with a spray drying method and tested for catalytic performance using partial oxidation of methane and steam reforming. The relationships between catalytic performance and structure were then investigated using X-ray diffraction, transmission electron microscopy, and environmental transmission electron microscopy. The possibility of solid solutions, segregated phases, and surface layers of Ni were explored. Results for a 10 at.% Ni in CeO2 catalyst reveal a poor catalytic behavior while a 20 at.% Ni in CeO2 catalyst is shown to have superior activity. The inclusion of both 10 at.% Gd and 10 at.% Ni in CeO2 enhances the catalytic performance. Analysis of the presence of Ni in all 3 samples reveals Ni heterogeneity and little evidence for extensive solid solution doping. Ni is found in small domains throughout CeO2 particles. In the 20 at.% Ni sample a segregated, catalytically active NiO phase is observed. Overall, it is found that significant interaction between Ni and CeO2 occurs that could affect the synthesis and functionality of the SOFC anode.
ContributorsCavendish, Rio (Author) / Crozier, Peter (Thesis advisor) / Adams, James (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Research literature was reviewed to find recommended tools and technologies for operating Unmanned Aerial Systems (UAS) fleets in an urban environment. However, restrictive legislation prohibits fully autonomous flight without an operator. Existing literature covers considerations for operating UAS fleets in a controlled environment, with an emphasis on the effect different networking approaches have on the topology of the UAS network. The primary network topology used to implement UAS communications is 802.11 protocols, which can transmit telemetry and a video stream using off the shelf hardware. Other implementations use low-frequency radios for long distance communication, or higher latency 4G LTE modems to access existing network infrastructure. However, a gap remains testing different network topologies outside of a controlled environment.
With the correct permits in place, further research can explore how different UAS network topologies behave in an urban environment when implemented with off the shelf UAS hardware. In addition to testing different network topologies, this thesis covers the implementation of building a secure, scalable system using modern cloud computation tools and services capable of supporting a variable number of UAS. The system also supports the end-to-end simulation of the system considering factors such as battery life and realistic UAS kinematics. The implementation of the system leads to new findings needed to deploy UAS fleets in urban environments.
With the correct permits in place, further research can explore how different UAS network topologies behave in an urban environment when implemented with off the shelf UAS hardware. In addition to testing different network topologies, this thesis covers the implementation of building a secure, scalable system using modern cloud computation tools and services capable of supporting a variable number of UAS. The system also supports the end-to-end simulation of the system considering factors such as battery life and realistic UAS kinematics. The implementation of the system leads to new findings needed to deploy UAS fleets in urban environments.
ContributorsD'Souza, Daniel (Author) / Panchanathan, Sethuraman (Thesis advisor) / Berman, Spring (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Autonomous Vehicle (AV), also known as self-driving car, promises to be a game changer for the transportation industry. This technology is predicted to drastically reduce the number of traffic fatalities due to human error [21].
However, road driving at any reasonable speed involves some risks. Therefore, even with high-tech AV algorithms and sophisticated sensors, there may be unavoidable crashes due to imperfection of the AV systems, or unexpected encounters with wildlife, children and pedestrians. Whenever there is a risk involved, there is the need for an ethical decision to be made [33].
While ethical and moral decision-making in humans has long been studied by experts, the advent of artificial intelligence (AI) also calls for machine ethics. To study the different moral and ethical decisions made by humans, experts may use the Trolley Problem [34], which is a scenario where one must pull a switch near a trolley track to redirect the trolley to kill one person on the track or do nothing, which will result in the deaths of five people. While it is important to take into account the input of members of a society and perform studies to understand how humans crash during unavoidable accidents to help program moral and ethical decision-making into self-driving cars, using the classical trolley problem is not ideal, as it is unrealistic and does not represent moral situations that people face in the real world.
This work seeks to increase the realism of the classical trolley problem for use in studies on moral and ethical decision-making by simulating realistic driving conditions in an immersive virtual environment with unavoidable crash scenarios, to investigate how drivers crash during these scenarios. Chapter 1 gives an in-depth background into autonomous vehicles and relevant ethical and moral problems; Chapter 2 describes current state-of-the-art online tools and simulators that were developed to study moral decision-making during unavoidable crashes. Chapters 3 focuses on building the simulator and the design of the crash scenarios. Chapter 4 describes human subjects experiments that were conducted with the simulator and their results, and Chapter 5 provides conclusions and avenues for future work.
However, road driving at any reasonable speed involves some risks. Therefore, even with high-tech AV algorithms and sophisticated sensors, there may be unavoidable crashes due to imperfection of the AV systems, or unexpected encounters with wildlife, children and pedestrians. Whenever there is a risk involved, there is the need for an ethical decision to be made [33].
While ethical and moral decision-making in humans has long been studied by experts, the advent of artificial intelligence (AI) also calls for machine ethics. To study the different moral and ethical decisions made by humans, experts may use the Trolley Problem [34], which is a scenario where one must pull a switch near a trolley track to redirect the trolley to kill one person on the track or do nothing, which will result in the deaths of five people. While it is important to take into account the input of members of a society and perform studies to understand how humans crash during unavoidable accidents to help program moral and ethical decision-making into self-driving cars, using the classical trolley problem is not ideal, as it is unrealistic and does not represent moral situations that people face in the real world.
This work seeks to increase the realism of the classical trolley problem for use in studies on moral and ethical decision-making by simulating realistic driving conditions in an immersive virtual environment with unavoidable crash scenarios, to investigate how drivers crash during these scenarios. Chapter 1 gives an in-depth background into autonomous vehicles and relevant ethical and moral problems; Chapter 2 describes current state-of-the-art online tools and simulators that were developed to study moral decision-making during unavoidable crashes. Chapters 3 focuses on building the simulator and the design of the crash scenarios. Chapter 4 describes human subjects experiments that were conducted with the simulator and their results, and Chapter 5 provides conclusions and avenues for future work.
ContributorsKankam, Immanuella (Author) / Berman, Spring (Thesis advisor) / Johnson, Kathryn (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2019
Description
The construction industry is very mundane and tiring for workers without the assistance of machines. This challenge has changed the trend of construction industry tremendously by motivating the development of robots that can replace human workers. This thesis presents a computed torque controller that is designed to produce movements by a small-scale, 5 degree-of-freedom (DOF) robotic arm that are useful for construction operations, specifically bricklaying. A software framework for the robotic arm with motion and path planning features and different control capabilities has also been developed using the Robot Operating System (ROS).
First, a literature review of bricklaying construction activity and existing robots’ performance is discussed. After describing an overview of the required robot structure, a mathematical model is presented for the 5-DOF robotic arm. A model-based computed torque controller is designed for the nonlinear dynamic robotic arm, taking into consideration the dynamic and kinematic properties of the arm. For sustainable growth of this technology so that it is affordable to the masses, it is important that the energy consumption by the robot is optimized. In this thesis, the trajectory of the robotic arm is optimized using sequential quadratic programming. The results of the energy optimization procedure are also analyzed for different possible trajectories.
A construction testbed setup is simulated in the ROS platform to validate the designed controllers and optimized robot trajectories on different experimental scenarios. A commercially available 5-DOF robotic arm is modeled in the ROS simulators Gazebo and Rviz. The path and motion planning is performed using the Moveit-ROS interface and also implemented on a physical small-scale robotic arm. A Matlab-ROS framework for execution of different controllers on the physical robot is described. Finally, the results of the controller simulation and experiments are discussed in detail.
First, a literature review of bricklaying construction activity and existing robots’ performance is discussed. After describing an overview of the required robot structure, a mathematical model is presented for the 5-DOF robotic arm. A model-based computed torque controller is designed for the nonlinear dynamic robotic arm, taking into consideration the dynamic and kinematic properties of the arm. For sustainable growth of this technology so that it is affordable to the masses, it is important that the energy consumption by the robot is optimized. In this thesis, the trajectory of the robotic arm is optimized using sequential quadratic programming. The results of the energy optimization procedure are also analyzed for different possible trajectories.
A construction testbed setup is simulated in the ROS platform to validate the designed controllers and optimized robot trajectories on different experimental scenarios. A commercially available 5-DOF robotic arm is modeled in the ROS simulators Gazebo and Rviz. The path and motion planning is performed using the Moveit-ROS interface and also implemented on a physical small-scale robotic arm. A Matlab-ROS framework for execution of different controllers on the physical robot is described. Finally, the results of the controller simulation and experiments are discussed in detail.
ContributorsGandhi, Sushrut (Author) / Berman, Spring (Thesis advisor) / Marvi, Hamidreza (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2019
Description
This work considers the design of separating input signals in order to discriminate among a finite number of uncertain nonlinear models. Each nonlinear model corresponds to a system operating mode, unobserved intents of other drivers or robots, or to fault types or attack strategies, etc., and the separating inputs are designed such that the output trajectories of all the nonlinear models are guaranteed to be distinguishable from each other under any realization of uncertainties in the initial condition, model discrepancies or noise. I propose a two-step approach. First, using an optimization-based approach, we over-approximate nonlinear dynamics by uncertain affine models, as abstractions that preserve all its system behaviors such that any discrimination guarantees for the affine abstraction also hold for the original nonlinear system. Then, I propose a novel solution in the form of a mixed-integer linear program (MILP) to the active model discrimination problem for uncertain affine models, which includes the affine abstraction and thus, the nonlinear models. Finally, I demonstrate the effectiveness of our approach for identifying the intention of other vehicles in a highway lane changing scenario. For the abstraction, I explore two approaches. In the first approach, I construct the bounding planes using a Mixed-Integer Nonlinear Problem (MINLP) formulation of the given system with appropriately designed constraints. For the second approach, I solve a linear programming (LP) problem that over-approximates the nonlinear function at only the grid points of a mesh with a given resolution and then accounting for the entire domain via an appropriate correction term. To achieve a desired approximation accuracy, we also iteratively subdivide the domain into subregions. This method applies to nonlinear functions with different degrees of smoothness, including Lipschitz continuous functions, and improves on existing approaches by enabling the use of tighter bounds. Finally, we compare the effectiveness of this approach with the existing optimization-based methods in simulation and illustrate its applicability for estimator design.
ContributorsSingh, Kanishka Raj (Author) / Yong, Sze Zheng (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2018
Description
This thesis presents an autonomous vehicle test bed which can be used to conduct studies on the interaction between human-driven vehicles and autonomous vehicles on the road. The test bed will make use of a fleet of robots which is a microcosm of an autonomous vehicle performing all the vital tasks like lane following, traffic signal obeying and collision avoidance with other vehicles on the road. The robots use real-time image processing and closed-loop control techniques to achieve automation. The testbed also features a manual control mode where a user can choose to control the car with a joystick by viewing a video relayed to the control station. Stochastic rogue vehicle processes will be introduced into the system which will emulate random behaviors in an autonomous vehicle. The test bed was experimented to perform a comparative study of driving capabilities of the miniature self-driving car and a human driver.
ContributorsSubramanyam, Rakshith (Author) / Berman, Spring (Thesis advisor) / Yu, Honbin (Thesis advisor) / Jayasurya, Suren (Committee member) / Arizona State University (Publisher)
Created2018
Description
In this thesis, different H∞ observers for time-delay systems are implemented and
their performances are compared. Equations that can be used to calculate observer gains are mentioned. Different methods that can be used to implement observers for time-delay systems are illustrated. Various stable and unstable systems are used and H∞ bounds are calculated using these observer designing methods. Delays are assumed to be known constants for all systems. H∞ gains are calculated numerically using disturbance signals and performances of observers are compared.
The primary goal of this thesis is to implement the observer for Time Delay Systems designed using SOS and compare its performance with existing H∞ optimal observers. These observers are more general than other observers for time-delay systems as they make corrections to the delayed state as well along with the present state. The observer dynamics can be represented by an ODE coupled with a PDE. Results shown in this thesis show that this type of observers performs better than other H∞ observers. Sub-optimal observer-based state feedback system is also generated and simulated using the SOS observer. The simulation results show that the closed loop system converges very quickly, and the observer can be used to design full state-feedback closed loop system.
their performances are compared. Equations that can be used to calculate observer gains are mentioned. Different methods that can be used to implement observers for time-delay systems are illustrated. Various stable and unstable systems are used and H∞ bounds are calculated using these observer designing methods. Delays are assumed to be known constants for all systems. H∞ gains are calculated numerically using disturbance signals and performances of observers are compared.
The primary goal of this thesis is to implement the observer for Time Delay Systems designed using SOS and compare its performance with existing H∞ optimal observers. These observers are more general than other observers for time-delay systems as they make corrections to the delayed state as well along with the present state. The observer dynamics can be represented by an ODE coupled with a PDE. Results shown in this thesis show that this type of observers performs better than other H∞ observers. Sub-optimal observer-based state feedback system is also generated and simulated using the SOS observer. The simulation results show that the closed loop system converges very quickly, and the observer can be used to design full state-feedback closed loop system.
ContributorsTalati, Rushabh Vikram (Author) / Peet, Matthew (Thesis advisor) / Berman, Spring (Committee member) / Rivera, Daniel (Committee member) / Arizona State University (Publisher)
Created2018