ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Mechanical Engineering
- All Subjects: Biology
- Creators: Marvi, Hamid
Description
In this work, different passive prosthetic ankles are studied. It is observed that complicated designs increase the cost of production, but simple designs have limited functionality. A new design for a passive prosthetic ankle is presented that is simple to manufacture while having superior functionality. This prosthetic ankle design has two springs: one mimicking Achilles tendon and the other mimicking Anterior-Tibialis tendon. The dynamics of the prosthetic ankle is discussed and simulated using Working model 2D. The simulation results are used to optimize the springs stiffness. Two experiments are conducted using the developed ankle to verify the simulation It is found that this novel ankle design is better than Solid Ankle Cushioned Heel (SACH) foot. The experimental data is used to find the tendon and muscle activation forces of the subject wearing the prosthesis using OpenSim. A conclusion is included along with suggested future work.
ContributorsBhat, Sandesh Ganapati (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Lee, Hyuglae (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Basilisk lizard is known for its agile locomotion capabilities on granular and aquatic media making it an impressive model organism for studying multi-terrain locomotion mechanics. The work presented here is aimed at understanding locomotion characteristics of Basilisk lizards through a systematic series of robotic and animal experiments. In this work, a Basilisk lizard inspired legged robot with bipedal and quadrupedal locomotion capabilities is presented. A series of robot experiments are conducted on dry and wet (saturated) granular media to determine the effects of gait parameters and substrate saturation, on robot velocity and energetics. Gait parameters studied here are stride frequency and stride length. Results of robot experiments are compared with previously obtained animal data. It is observed that for a fixed robot stride frequency, velocity and stride length increase with increasing saturation, confirming the locomotion characteristics of the Basilisk lizard. It is further observed that with increasing saturation level, robot cost of transport decreases. An identical series of robot experiments are performed with quadrupedal gait to determine effects of gait parameters on robot performance. Generally, energetics of bipedal running is observed to be higher than quadrupedal operation. Experimental results also reveal how gait parameters can be varied to achieve different desired velocities depending on the substrate saturation level. In addition to robot experiments on granular media, a series of animal experiments are conducted to determine and characterize strategies
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
ContributorsJayanetti, Vidu (Author) / Marvi, Hamid (Thesis advisor) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2018
Description
Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the development of robot controllers and system architectures that scale well with the number of robots and that are robust to robot errors and failures. To achieve this, one approach is to design decentralized robot control policies that require only local sensing and local, ad-hoc communication. In particular, stochastic control policies can be designed that are agnostic to individual robot identities and do not require a priori information about the environment or sophisticated computation, sensing, navigation, or communication capabilities. This dissertation presents novel swarm control strategies with these properties for detecting and mapping static targets, which represent features of interest, in an
unknown, bounded, obstacle-free environment. The robots move on a finite spatial grid according to
the time-homogeneous transition probabilities of a Discrete-Time Discrete-State (DTDS) Markov chain model, and they exchange information with other robots within their communication range using a consensus (agreement) protocol. This dissertation extend theoretical guarantees on multi-robot consensus over fixed and time-varying communication networks with known connectivity properties to consensus over the networks that have Markovian switching dynamics and no presumed connectivity. This dissertation develops such swarm consensus strategies for detecting a single feature in the environment, tracking multiple features, and reconstructing a discrete distribution of features modeled as an occupancy grid map.
The proposed consensus approaches are validated in numerical simulations and in 3D physics-based simulations of quadrotors in Gazebo. The scalability of the proposed approaches is examined through extensive numerical simulation studies over different swarm populations and environment sizes.
ContributorsShirsat, Aniket (Author) / Berman, Spring (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Saripalli, Srikanth (Committee member) / Gharavi, Lance (Committee member) / Arizona State University (Publisher)
Created2022
Description
While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms have shown promising results for sensor fusion with wearable robots, however, they require extensive data to train models for different users and experimental conditions. Modeling soft sensors and actuators require characterizing non-linearity and hysteresis, which complicates deriving an analytical model. Experimental characterization can capture the characteristics of non-linearity and hysteresis but requires developing a synthesized model for real-time control. Controllers for wearable soft robots must be robust to compensate for unknown disturbances that arise from the soft robot and its interaction with the user. Since developing dynamic models for soft robots is complex, inaccuracies that arise from the unmodeled dynamics lead to significant disturbances that the controller needs to compensate for. In addition, obtaining a physical model of the human-robot interaction is complex due to unknown human dynamics during walking. Finally, the performance of soft robots for wearable applications requires extensive experimental evaluation to analyze the benefits for the user. To address these challenges, this dissertation focuses on the sensing, modeling, control and evaluation of soft robots for wearable applications. A model-based sensor fusion algorithm is proposed to improve the estimation of human joint kinematics, with a soft flexible robot that requires compact and lightweight sensors. To overcome limitations with rigid sensors, an inflatable soft haptic sensor is developed to enable gait sensing and haptic feedback. Through experimental characterization, a mathematical model is derived to quantify the user's ground reaction forces and the delivered haptic force. Lastly, the performance of a wearable soft exosuit in assisting human users during lifting tasks is evaluated, and the benefits obtained from the soft robot assistance are analyzed.
ContributorsQuiñones Yumbla, Emiliano (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
Regolith excavation systems are the enabling technology that must be developed in order to implement many of the plans for in-situ resource utilization (ISRU) that have been developed in recent years to aid in creating a lasting human presence on the surface of the Moon, Mars, and other celestial bodies. The majority of proposed ISRU excavation systems are integrated onto a wheeled mobility system, however none yet have proposed the use of a screw-propelled vehicle, which has the potential to augment and enhance the capabilities of the excavation system. As a result, CASPER, a novel screw-propelled excavation rover is developed and analyzed to determine its effectiveness as a ISRU excavation system. The excavation rate, power, velocity, cost of transport, and a new parameter, excavation transport rate, are analyzed for various configurations of the vehicle through mobility and excavation tests performed in silica sand. The optimal configuration yielded a 28.4 kg/hr excavation rate and11.2 m/min traverse rate with an overall system mass of 3.4 kg and power draw of26.3 W. CASPER’s mobility and excavation performance results are compared to four notable proposed ISRU excavation systems of various types. The results indicate that this architecture shows promise as an ISRU excavator because it provides significant excavation capability with low mass and power requirements.
ContributorsGreen, Marko (Author) / Marvi, Hamid (Thesis advisor) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2021
Description
Many medical procedures, like surgeries, deal with the physical manipulation of sensitive internal tissues. Over time, new medical tools and techniques have been developed to improve the safety and efficacy of these procedures. Despite the leaps and bounds of progress made up to the present day, three major obstacles (among others) persist, bleeding, pain, and the risk of infection. Advances in minimally invasive treatments have transformed many formerly risky surgical procedures into very safe and highly successful routines. Minimally invasive surgeries are characterized by small incision profiles compared to the large incisions in open surgeries, minimizing the aforementioned issues. Minimally invasive procedures lead to several benefits, such as shorter recovery time, fewer complications, and less postoperative pain. In minimally invasive surgery, doctors use various techniques to operate with less damage to the body than open surgery. Today, these procedures have an established, successful history and promising future. Steerable needles are one of the tools proposed for minimally invasive operations. Needle steering is a method for guiding a long, flexible needle through curved paths to reach targets deep in the body, eliminating the need for large incisions. In this dissertation, we present a new needle steering technology: magnetic needle steering. This technology is proposed to address the limitations of conventional needle steering that hindered its clinical applications. Magnetic needle steering eliminates excessive tissue damage, restrictions of the minimum radius of curvature, and the need for a complex nonlinear model, to name a few. It also allows fabricating the needle shaft out of soft and tissue-compliant materials.
This is achieved by first developing an electromagnetic coil system capable of producing desired magnetic fields and gradients; then, a magnetically actuated needle is designed, and its effectiveness is experimentally evaluated. Afterward, the scalability of this technique was tested using permanent magnets controlled with a robotic arm.
Furthermore, different configurations of permanent magnets and their influence on the magnetic field are investigated, enabling the possibility of designing a desired magnetic field for a specific surgical procedure and operation on a particular organ. Finally, potential future directions towards animal studies and clinical trials are discussed.
ContributorsIlami, Mahdi (Author) / Marvi, Hamid (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Nikkhah, Mehdi (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2021
Description
As the explorations beyond the Earth's boundaries continue to evolve, researchers and engineers strive to develop versatile technologies capable of adapting to unknown space conditions. For instance, the utilization of Screw-Propelled Vehicles (SPVs) and robotics that utilize helical screws propulsion to transverse planetary bodies is a growing area of interest. An example of such technology is the Extant Exobiology Life Surveyor (EELS), a snake-like robot currently developed by the NASA Jet Propulsion Laboratory (JPL) to explore the surface of Saturn’s moon, Enceladus. However, the utilization of such a mechanism requires a deep and thorough understanding of screw mobility in uncertain conditions. The main approach to exploring screw dynamics and optimal design involves the utilization of Discrete Element Method (DEM) simulations to assess interactions and behavior of screws when interacting with granular terrains. In this investigation, the Simplified Johnson-Kendall-Roberts (SJKR) model is implemented into the utilized simulation environment to account for cohesion effects similar to what is experienced on celestial bodies like Enceladus. The model is verified and validated through experimental and theoretical testing. Subsequently, the performance characteristics of screws are explored under varying parameters, such as thread depth, number of screw starts, and the material’s cohesion level. The study has examined significant relationships between the parameters under investigation and their influence on the screw performance.
ContributorsAbdelrahim, Mohammad (Author) / Marvi, Hamid (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2023
Description
Walking and mobility are essential aspects of our daily lives, enabling us to engage in various activities. Gait disorders and impaired mobility are widespread challenges faced by older adults and people with neurological injuries, as these conditions can significantly impact their quality of life, leading to a loss of independence and an increased risk of mortality. In response to these challenges, rehabilitation, and assistive robotics have emerged as promising alternatives to conventional gait therapy, offering potential solutions that are less labor-intensive and costly. Despite numerous advances in wearable lower-limb robotics, their current applicability remains confined to laboratory settings. To expand their utility to broader gait impairments and daily living conditions, there is a pressing need for more intelligent robot controllers. In this dissertation, these challenges are tackled from two perspectives: First, to improve the robot's understanding of human motion and intentions which is crucial for assistive robot control, a robust human locomotion estimation technique is presented, focusing on measuring trunk motion. Employing an invariant extended Kalman filtering method that takes sensor misplacement into account, improved convergence properties over the existing methods for different locomotion modes are shown. Secondly, to enhance safe and effective robot-aided gait training, this dissertation proposes to directly learn from physical therapists' demonstrations of manual gait assistance in post-stroke rehabilitation.
Lower-limb kinematics of patients and assistive force applied by therapists to the patient's leg are measured using a wearable sensing system which includes a custom-made force sensing array. The collected data is then used to characterize a therapist's strategies. Preliminary analysis indicates that knee extension and weight-shifting play pivotal roles in shaping a therapist's assistance strategies, which are then incorporated into a virtual impedance model that effectively captures high-level therapist behaviors throughout a complete training session. Furthermore, to introduce safety constraints in the design of such controllers, a safety-critical learning framework is explored through theoretical analysis and simulations. A safety filter incorporating an online iterative learning component is introduced to bring robust safety guarantees for gait robotic assistance and training, addressing challenges such as stochasticity and the absence of a known prior dynamic model.
ContributorsRezayat Sorkhabadi, Seyed Mostafa (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023