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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- Creators: Zhang, Wenlong
Description
What if there is a way to integrate prosthetics seamlessly with the human body and robots could help improve the lives of children with disabilities? With physical human-robot interaction being seen in multiple aspects of life, including industry, medical, and social, how these robots are interacting with human becomes even more important. Therefore, how smoothly the robot can interact with a person will determine how safe and efficient this relationship will be. This thesis investigates adaptive control method that allows a robot to adapt to the human's actions based on the interaction force. Allowing the relationship to become more effortless and less strained when the robot has a different goal than the human, as seen in Game Theory, using multiple techniques that adapts the system. Few applications this could be used for include robots in physical therapy, manufacturing robots that can adapt to a changing environment, and robots teaching people something new like dancing or learning how to walk after surgery.
The experience gained is the understanding of how a cost function of a system works, including the tracking error, speed of the system, the robot’s effort, and the human’s effort. Also, this two-agent system, results into a two-agent adaptive impedance model with an input for each agent of the system. This leads to a nontraditional linear quadratic regulator (LQR), that must be separated and then added together. Thus, creating a traditional LQR. This new experience can be used in the future to help build better safety protocols on manufacturing robots. In the future the knowledge learned from this research could be used to develop technologies for a robot to allow to adapt to help counteract human error.
The experience gained is the understanding of how a cost function of a system works, including the tracking error, speed of the system, the robot’s effort, and the human’s effort. Also, this two-agent system, results into a two-agent adaptive impedance model with an input for each agent of the system. This leads to a nontraditional linear quadratic regulator (LQR), that must be separated and then added together. Thus, creating a traditional LQR. This new experience can be used in the future to help build better safety protocols on manufacturing robots. In the future the knowledge learned from this research could be used to develop technologies for a robot to allow to adapt to help counteract human error.
ContributorsBell, Rebecca C (Author) / Zhang, Wenlong (Thesis advisor) / Chiou, Erin (Committee member) / Aukes, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
The knee joint has essential functions to support the body weight and maintain normal walking. Neurological diseases like stroke and musculoskeletal disorders like osteoarthritis can affect the function of the knee. Besides physical therapy, robot-assisted therapy using wearable exoskeletons and exosuits has shown the potential as an efficient therapy that helps patients restore their limbs’ functions. Exoskeletons and exosuits are being developed for either human performance augmentation or medical purposes like rehabilitation. Although, the research on exoskeletons started early before exosuits, the research and development on exosuits have recently grown rapidly as exosuits have advantages that exoskeletons lack. The objective of this research is to develop a soft exosuit for knee flexion assistance and validate its ability to reduce the EMG activity of the knee flexor muscles. The exosuit has been developed with a novel soft fabric actuator and novel 3D printed adjustable braces to attach the actuator aligned with the knee. A torque analytical model has been derived and validate experimentally to characterize and predict the torque output of the actuator. In addition to that, the actuator’s deflation and inflation time has been experimentally characterized and a controller has been implemented and the exosuit has been tested on a healthy human subject. It is found that the analytical torque model succeeded to predict the torque output in flexion angle range from 0° to 60° more precisely than analytical models in the literature. Deviations existed beyond 60° might have happened because some factors like fabric extensibility and actuator’s bending behavior. After human testing, results showed that, for the human subject tested, the exosuit gave the best performance when the controller was tuned to inflate at 31.9 % of the gait cycle. At this inflation timing, the biceps femoris, the semitendinosus and the vastus lateralis muscles showed average electromyography (EMG) reduction of - 32.02 %, - 23.05 % and - 2.85 % respectively. Finally, it is concluded that the developed exosuit may assist the knee flexion of more diverse healthy human subjects and it may potentially be used in the future in human performance augmentation and rehabilitation of people with disabilities.
ContributorsHasan, Ibrahim Mohammed Ibrahim (Author) / Zhang, Wenlong (Thesis advisor) / Aukes, Daniel (Committee member) / McDaniel, Troy (Committee member) / Arizona State University (Publisher)
Created2021