Matching Items (193)
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Description
The goal of this thesis is designing controllers for swarm robots transport a payload over inclines. Several fields of study are related to this study, including control theory, dynamic modeling and programming. MATLAB, a tool of design controller and simulation, is used in this thesis.

To achieve this goal,

The goal of this thesis is designing controllers for swarm robots transport a payload over inclines. Several fields of study are related to this study, including control theory, dynamic modeling and programming. MATLAB, a tool of design controller and simulation, is used in this thesis.

To achieve this goal, a model of swarm robots transportation should be designed, which is cruise control for this scenario. Secondly, based on free body diagram, force equilibrium equation can be deduced. Then, the function of plant can be deduced based on cruise control and force equilibrium equations. Thirdly, list potential controllers, which may implement desired controls of swarm robots, and test their performance. Modify value of gains and do simulations of these controller. After analyzing results of simulation, the best controller can be selected.

In the last section, there is conclusion of entire thesis project and pointing out future work. The section of future work will mention potential difficulties of building entire control system, which allow swarm robots transport over inclines in real environment.
ContributorsShe, Hanyu (Author) / Berman, Spring (Thesis director) / Marvi, Hamidreza (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Traditional wheeled robots struggle to traverse granular media such as sand or mud which has inspired the use of continuous tracks, legged, and various bio-inspired designs in recent robotics research. Animals can navigate the natural world with relative ease and one animal, the Basilisk lizard, can perform the amazing feat

Traditional wheeled robots struggle to traverse granular media such as sand or mud which has inspired the use of continuous tracks, legged, and various bio-inspired designs in recent robotics research. Animals can navigate the natural world with relative ease and one animal, the Basilisk lizard, can perform the amazing feat of bipedal water and land running. Through the observation and study of basilisk lizards of the common and plumed variety, inspiration and development of a robotic platform was completed. After fabricating the bio-inspired robot, parameters unchanged by the animals were varied to characterize the combined effects of stride length and frequency on average velocity. It was found that animals increased stride length at higher saturation levels of sand to increase their velocity rather than increase their step frequency. The BasiliskBot version one was unable to change its stride length as the wheel-legs or "whegs" of this version were set at four spokes. Bipedal running of the robot was slower than quadrupedal running due to sand reaction forces and tail drag. BasiliskBot version two was lighter than the first version and had a range of stride lengths tested with increasing spoke numbers from 3-7. At lower step frequencies and lower wheg numbers, higher average velocity could be achieved compared to higher wheg numbers despite the highest maximum velocity being achieved by the highest number of spokes. A comparison of transition strategies for common and plumed basilisks showed both species chose to jump and swim through water more often than jump and run across water which achieved the highest average velocity. Results of transition strategies study pertain to future developments of the robot for amphibious purposes. Weight experiments were performed to assess the ability of the robot to carry sensors and other payloads. Added weight increased the highest frequency allowable before failure, but also caused failure at low step frequencies that had not displayed failure previously.
ContributorsBurch, Hailey (Author) / Marvi, Hamidreza (Thesis director) / Bagheri, Hosain (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Current robotic systems are limited in their abilities to efficiently traverse granular environments due to an underdeveloped understanding of the physics governing the interactions between solids and deformable substrates. As there are many animal species biologically designed for navigation of specific terrains, it is useful to study their mechanical ground

Current robotic systems are limited in their abilities to efficiently traverse granular environments due to an underdeveloped understanding of the physics governing the interactions between solids and deformable substrates. As there are many animal species biologically designed for navigation of specific terrains, it is useful to study their mechanical ground interactions, and the kinematics of their movement. To achieve this, an automated, fluidized bed was designed to simulate various terrains under different conditions for animal testing. This document examines the design process of this test setup, with a focus on the controls. Control programs will be tested with hardware to ensure full functionality of the design. Knowledge gained from these studies can be used to optimize morphologies and gait parameters of robots. Ultimately, a robot can be developed that is capable of adapting itself for efficient locomotion on any terrain. These systems will be invaluable for applications such as planet exploration and rescue operations.
ContributorsHarvey, Carolyn Jean (Author) / Marvi, Hamidreza (Thesis director) / Emady, Heather (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Admittance control with fixed damping has been a successful control strategy in previous human-robotic interaction research. This research implements a variable damping admittance controller in a 7-DOF robotic arm coupled with a human subject’s arm at the end effector to study the trade-off of agility and stability and

Admittance control with fixed damping has been a successful control strategy in previous human-robotic interaction research. This research implements a variable damping admittance controller in a 7-DOF robotic arm coupled with a human subject’s arm at the end effector to study the trade-off of agility and stability and aims to produce a control scheme which displays both fast rise time and stability. The variable damping controller uses a measure of intent of movement to vary damping to aid the user’s movement to a target. The range of damping values is bounded by incorporating knowledge of a human arm to ensure the stability of the coupled human-robot system. Human subjects completed experiments with fixed positive, fixed negative, and variable damping controllers to evaluate the variable damping controller’s ability to increase agility and stability. Comparisons of the two fixed damping controllers showed as fixed damping increased, the coupled human-robot system reacted with less overshoot at the expense of rise time, which is used as a measure of agility. The inverse was also true; as damping became increasingly negative, the overshoot and stability of the system was compromised, while the rise time became faster. Analysis of the variable damping controller demonstrated humans could extract the benefits of the variable damping controller in its ability to increase agility in comparison to a positive damping controller and increase stability in comparison to a negative damping controller.
ContributorsBitz, Tanner Jacob (Author) / Lee, Hyunglae (Thesis advisor) / Marvi, Hamidreza (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Fraud is defined as the utilization of deception for illegal gain by hiding the true nature of the activity. While organizations lose around $3.7 trillion in revenue due to financial crimes and fraud worldwide, they can affect all levels of society significantly. In this dissertation, I focus on credit card

Fraud is defined as the utilization of deception for illegal gain by hiding the true nature of the activity. While organizations lose around $3.7 trillion in revenue due to financial crimes and fraud worldwide, they can affect all levels of society significantly. In this dissertation, I focus on credit card fraud in online transactions. Every online transaction comes with a fraud risk and it is the merchant's liability to detect and stop fraudulent transactions. Merchants utilize various mechanisms to prevent and manage fraud such as automated fraud detection systems and manual transaction reviews by expert fraud analysts. Many proposed solutions mostly focus on fraud detection accuracy and ignore financial considerations. Also, the highly effective manual review process is overlooked. First, I propose Profit Optimizing Neural Risk Manager (PONRM), a selective classifier that (a) constitutes optimal collaboration between machine learning models and human expertise under industrial constraints, (b) is cost and profit sensitive. I suggest directions on how to characterize fraudulent behavior and assess the risk of a transaction. I show that my framework outperforms cost-sensitive and cost-insensitive baselines on three real-world merchant datasets. While PONRM is able to work with many supervised learners and obtain convincing results, utilizing probability outputs directly from the trained model itself can pose problems, especially in deep learning as softmax output is not a true uncertainty measure. This phenomenon, and the wide and rapid adoption of deep learning by practitioners brought unintended consequences in many situations such as in the infamous case of Google Photos' racist image recognition algorithm; thus, necessitated the utilization of the quantified uncertainty for each prediction. There have been recent efforts towards quantifying uncertainty in conventional deep learning methods (e.g., dropout as Bayesian approximation); however, their optimal use in decision making is often overlooked and understudied. Thus, I present a mixed-integer programming framework for selective classification called MIPSC, that investigates and combines model uncertainty and predictive mean to identify optimal classification and rejection regions. I also extend this framework to cost-sensitive settings (MIPCSC) and focus on the critical real-world problem, online fraud management and show that my approach outperforms industry standard methods significantly for online fraud management in real-world settings.
ContributorsYildirim, Mehmet Yigit (Author) / Davulcu, Hasan (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Huang, Dijiang (Committee member) / Hsiao, Ihan (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Building and optimizing a design for deformable media can be extremely costly. However, granular scaling laws enable the ability to predict system velocity and mobility power consumption by testing at a smaller scale in the same environment. The validity of the granular scaling laws for arbitrarily shaped wheels and screws

Building and optimizing a design for deformable media can be extremely costly. However, granular scaling laws enable the ability to predict system velocity and mobility power consumption by testing at a smaller scale in the same environment. The validity of the granular scaling laws for arbitrarily shaped wheels and screws were evaluated in materials like silica sand and BP-1, a lunar simulant. Different wheel geometries, such as non-grousered and straight and bihelically grousered wheels were created and tested using 3D printed technologies. Using the granular scaling laws and the empirical data from initial experiments, power and velocity were predicted for a larger scaled version then experimentally validated on a dynamic mobility platform. Working with granular media has high variability in material properties depending on initial environmental conditions, so particular emphasis was placed on consistency in the testing methodology. Through experiments, these scaling laws have been validated with defined use cases and limitations.
ContributorsMcbryan, Teresa (Author) / Marvi, Hamidreza (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Tubes and pipelines serve as a major component of several units in power plants and oil, gas, and water transmission. These structures undergo extreme conditions, where temperature and pressure vary, leading to corroding of the pipe over time, creating defects in them. A small crack in these tubes can cause

Tubes and pipelines serve as a major component of several units in power plants and oil, gas, and water transmission. These structures undergo extreme conditions, where temperature and pressure vary, leading to corroding of the pipe over time, creating defects in them. A small crack in these tubes can cause major safety problems, so a regular inspection of these tubes is required. Most power plants prefer to use non-destructive testing procedures, such as long-range ultrasonic testing and phased array ultrasonic testing, to name a few. These procedures can be carried out with the help of crawlers that go inside the pipes. One of the main drawbacks of the current robotic tube inspection robots is the lack of maneuverability over complex tubular structures and the inability to traverse non-ferromagnetic pipelines. The main motivation of this project is to create a robotic system that can grab onto ferromagnetic and non-ferromagnetic tubes and move along those, move onto adjacent tubes, and maneuver around flanges and bends in the tube. Furthermore, most of the robots used for inspection rely on roller balls and suction-based components that can allow the robot to hold on to the curved surface of the tube. These techniques fail when the surface is rough or uneven, which has served as an inspiration to look at friction-based solutions. Lizards are known for their agile locomotion, as well as their ability to grab on any surface irrespective of the surface texture. The work presented here is focused on the design and control of a lizard-inspired tube inspection robot that can be used to inspect complex tubular structures made of any material.
ContributorsMasurkar, Nihar Dattaram (Author) / Marvi, Hamidreza (Thesis advisor) / Dehghan-Niri, Ehsan (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Realizing the applications of Internet of Things (IoT) with the goal of achieving a more efficient and automated world requires billions of connected smart devices and the minimization of hardware cost in these devices. As a result, many IoT devices do not have sufficient resources to support various protocols required

Realizing the applications of Internet of Things (IoT) with the goal of achieving a more efficient and automated world requires billions of connected smart devices and the minimization of hardware cost in these devices. As a result, many IoT devices do not have sufficient resources to support various protocols required in many IoT applications. Because of this, new protocols have been introduced to support the integration of these devices. One of these protocols is the increasingly popular routing protocol for low-power and lossy networks (RPL). However, this protocol is well known to attract blackhole and sinkhole attacks and cause serious difficulties when using more computationally intensive techniques to protect against these attacks, such as intrusion detection systems and rank authentication schemes. In this paper, an effective approach is presented to protect RPL networks against blackhole attacks. The approach does not address sinkhole attacks because they cause low damage and are often used along blackhole attacks and can be detected when blackhole attaches are detected. This approach uses the feature of multiple parents per node and a parent evaluation system enabling nodes to select more reliable routes. Simulations have been conducted, compared to existing approaches this approach would provide better protection against blackhole attacks with much lower overheads for small RPL networks.
ContributorsSanders, Kent (Author) / Yau, Stephen S (Thesis advisor) / Huang, Dijiang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The ability for aerial manipulators to stay aloft while interacting with dynamic environments is critical for successfully in situ data acquisition methods in arboreal environments. One widely used platform utilizes a six degree of freedom manipulator attached to quadcoper or octocopter, to sample a tree leaf by maintaining the system

The ability for aerial manipulators to stay aloft while interacting with dynamic environments is critical for successfully in situ data acquisition methods in arboreal environments. One widely used platform utilizes a six degree of freedom manipulator attached to quadcoper or octocopter, to sample a tree leaf by maintaining the system in a hover while the arm pulls the leaf for a sample. Other system are comprised of simpler quadcopter with a fixed mechanical device to physically cut the leaf while the system is manually piloted. Neither of these common methods account or compensate for the variation of inherent dynamics occurring in the arboreal-aerial manipulator interaction effects. This research proposes force and velocity feedback methods to control an aerial manipulation platform while allowing waypoint navigation within the work space to take place. Using these methods requires minimal knowledge of the system and the dynamic parameters. This thesis outlines the Robot Operating System (ROS) based Open Autonomous Air Vehicle (OpenUAV) simulations performed on the purposed three degree of freedom redundant aerial manipulation platform.
ContributorsCohen, Daniel (Author) / Das, Jnaneshwar (Thesis advisor) / Marvi, Hamidreza (Committee member) / Saldaña, David (Committee member) / Arizona State University (Publisher)
Created2022
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Description本文对中国制药企业并购溢价影响因素进行了研究,提出了对制药企业并购非常重要的两个新的影响因素:可生产药品批文和在研新药批文。本文以2011年1月—2019年12月间我国制药行业上市公司并购事件为样本,对在研新药和可生产药品批文的价值从四个维度度量:是否有在研新药和可生产药品批文;在研新药数量及可生产药品批文数量;根据创新药和仿制药两个类别进行细分;标的企业所拥有的在研新药和可生产药品批文的市场价值。论文发现药品批文对企业并购溢价的影响不是很显著。进一步的,本文探究了药品批文对主并企业的对被并购公司的估值的影响。实证结果表明,我国制药企业在并购估值时确实会考虑到在研新药和可生产药品批文的价值。本文还发现对于可生产药品来说,相对创新药,被并购公司持有的仿制药批文影响更显著。而对于在研新药来说,主并企业更看重在研的创新药,在研仿制药对并购估值的影响不大。最后,本文选取了两个代表性案例进一步分析和探讨药品批文对企业并购的影响。
ContributorsYe, Tao (Author) / Shen, Wei (Thesis advisor) / Chang, Chun (Thesis advisor) / Jiang, Zhan (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2022