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Undulatory locomotion is a unique form of swimming that generates thrust through the propagation of a wave through a fish’s body. The proposed device utilizes a constrained compliant material with a single actuator to generate an undulatory motion. This paper draws inspiration from Anguilliformes and discusses the kinematics and dynamics

Undulatory locomotion is a unique form of swimming that generates thrust through the propagation of a wave through a fish’s body. The proposed device utilizes a constrained compliant material with a single actuator to generate an undulatory motion. This paper draws inspiration from Anguilliformes and discusses the kinematics and dynamics of wave propagation of an underwater robot. A variety of parameters are explored through modeling and are optimized for thrust generation to better understand the device. This paper validates the theoretical spine behavior through experimentation and provides a path forward for future development in device optimization for various applications. Previous work developed devices that utilized either paired soft actuators or multiple redundant classical actuators that resulted in a complex prototype with intricate controls. The work of this paper contrasts with prior work in that it aims to achieve undulatory motion through passive actuation from a single actively driven point which simplifies the control. Through this work, the goal is to further explore low-cost soft robotics via bistable mechanisms, continuum material properties, and simplified modeling practices.
ContributorsKwan, Anson (Author) / Aukes, Daniel (Thesis advisor) / Zhang, Wenlong (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Multibody Dynamic (MBD) models are important tools in motion analysis and are used to represent and accurately predict the behavior of systems in the real-world. These models have a range of applications, including the stowage and deployment of flexible deployables on spacecraft, the dynamic response of vehicles in automotive design

Multibody Dynamic (MBD) models are important tools in motion analysis and are used to represent and accurately predict the behavior of systems in the real-world. These models have a range of applications, including the stowage and deployment of flexible deployables on spacecraft, the dynamic response of vehicles in automotive design and crash testing, and mapping interactions of the human body. An accurate model can aid in the design of a system to ensure the system is effective and meets specified performance criteria when built. A model may have many design parameters, such as geometrical constraints and component mechanical properties, or controller parameters if the system uses an external controller. Varying these parameters and rerunning analyses by hand to find an ideal design can be time consuming for models that take hours or days to run. To reduce the amount of time required to find a set of parameters that produces a desired performance, optimization is necessary. Many papers have discussed methods for optimizing rigid and flexible MBD models, and separately their controllers, using both gradient-based and gradient-free algorithms. However, these optimization methods have not been used to optimize full-scale MBD models and their controllers simultaneously. This thesis presents a method for co-optimizing an MBD model and controller that allows for the flexibility to find model and controller-based solutions for systems with tightly coupled parameters. Specifically, the optimization is performed on a quadrotor drone MBD model undergoing disturbance from a slung load and its position controller to meet specified position error performance criteria. A gradient-free optimization algorithm and multiple objective approach is used due to the many local optima from the tradeoffs between the model and controller parameters. The thesis uses nine different quadrotor cases with three different position error formulations. The results are used to determine the effectiveness of the optimization and the ability to converge on a single optimal design. After reviewing the results, the optimization limitations are discussed as well as the ability to transition the optimization to work with different MBD models and their controllers.
ContributorsGambatese, Marcus (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Inoyama, Daisaku (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper

Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper gait cycle might be attributed to the lack of force produced at the toe-off stage. This project addresses if it is possible to create an OpenSim model to find the ideal time and force magnitude needed of an assistive force ankle device to improve gait patterns in individuals with NMD.
ContributorsRivera, Jose Luis (Author) / Zhang, Wenlong (Thesis director) / Lockhart, Thurmon (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05