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: Marvi, Hamidreza
Description
August Krogh, a 20th century Nobel Prize winner in Physiology and Medicine, once stated, "for such a large number of problems there will be some animal of choice, or a few such animals, on which it can be most conveniently studied." What developed to be known as the Krogh Principle, has become the cornerstone of bioinspired robotics. This is the realization that solutions to various multifaceted engineering problems lie in nature. With the integration of biology, physics and engineering, the classical approach in solving engineering problems has transformed. Through such an integration, the presented research will address the following engineering solution: maneuverability on and through complex granular and aquatic environments. The basilisk lizard and the octopus are the key sources of inspiration for the anticipated solution. The basilisk lizard is a highly agile reptile with the ability to easily traverse on vast, alternating, unstructured, and complex terrains (i.e. sand, mud, water). This makes them a great medium for pursuing potential solutions for robotic locomotion on such terrains. The octopus, with a nearly soft, yet muscular hydrostat body and arms, is proficient in locomotion and its complex motor functions are vast. Their versatility, "infinite" degrees of freedom, and dexterity have made them an ideal candidate for inspiration in the fields such as soft robotics. Through conducting animal experiments on the basilisk lizard and octopus, insight can be obtained on the question: how does the animal interact with complex granular and aquatic environments so effectively? Following it through by conducting systematic robotic experiments, the capabilities and limitations of the animal can be understood. Integrating the hierarchical concepts observed and learnt through animal and robotic experiments, it can be used towards designing, modeling, and developing robotic systems that will assist humanity and society on a diversified set of applications: home service, health care, public safety, transportation, logistics, structural examinations, aquatic and extraterrestrial exploration, search-and-rescue, environmental monitoring, forestry, and agriculture, just to name a few. By learning and being inspired by nature, there exist the potential to go beyond nature for the greater good of society and humanity.
ContributorsBagheri, Hosain (Author) / Marvi, Hamidreza (Thesis advisor) / Berman, Spring M (Committee member) / DeNardo, Dale F (Committee member) / Emady, Heather N (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2020
Description
In certain ant species, groups of ants work together to transport food and materials back to their nests. In some cases, the group exhibits a leader-follower behavior in which a single ant guides the entire group based on its knowledge of the destination. In some cases, the leader role is occupied temporarily by an ant, only to be replaced when an ant with new information arrives. This kind of behavior can be very useful in uncertain environments where robot teams work together to transport a heavy or bulky payload. The purpose of this research was to study ways to implement this behavior on robot teams.
In this work, I combined existing dynamical models of collective transport in ants to create a stochastic model that describes these behaviors and can be used to control multi-robot systems to perform collective transport. In this model, each agent transitions stochastically between roles based on the force that it senses the other agents are applying to the load. The agent’s motion is governed by a proportional controller that updates its applied force based on the load velocity. I developed agent-based simulations of this model in NetLogo and explored leader-follower scenarios in which agents receive information about the transport destination by a newly informed agent (leader) joining the team. From these simulations, I derived the mean allocations of agents between “puller” and “lifter” roles and the mean forces applied by the agents throughout the motion.
From the simulation results obtained, we show that the mean ratio of lifter to puller populations is approximately 1:1. We also show that agents using the role update procedure based on forces are required to exert less force than agents that select their role based on their position on the load, although both strategies achieve similar transport speeds.
In this work, I combined existing dynamical models of collective transport in ants to create a stochastic model that describes these behaviors and can be used to control multi-robot systems to perform collective transport. In this model, each agent transitions stochastically between roles based on the force that it senses the other agents are applying to the load. The agent’s motion is governed by a proportional controller that updates its applied force based on the load velocity. I developed agent-based simulations of this model in NetLogo and explored leader-follower scenarios in which agents receive information about the transport destination by a newly informed agent (leader) joining the team. From these simulations, I derived the mean allocations of agents between “puller” and “lifter” roles and the mean forces applied by the agents throughout the motion.
From the simulation results obtained, we show that the mean ratio of lifter to puller populations is approximately 1:1. We also show that agents using the role update procedure based on forces are required to exert less force than agents that select their role based on their position on the load, although both strategies achieve similar transport speeds.
ContributorsGah, Elikplim (Author) / Berman, Spring M (Thesis advisor, Committee member) / Pavlic, Theodore (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2020