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- All Subjects: Foldable
- Creators: Marvi, Hamid
- Creators: Downey, Matthew Evan
Description
The researchers build a drone with a grasping mechanism to wrap around branches to perch. The design process and methodology are discussed along with the software and hardware configuration. The researchers explain the influences on the design and the possibilities for what it could inspire.
ContributorsDowney, Matthew Evan (Co-author) / Macias, Jose (Co-author) / Goldenberg, Edward (Co-author) / Zhang, Wenlong (Thesis director) / Aukes, Daniel (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Existing robotic excavation research has been primarily focused on lunar mining missions or simple traffic control in confined tunnels, however little work attempts to bring collective excavation into the realm of human infrastructure. This thesis explores a decentralized approach to excavation processes, where traffic laws are borrowed from swarms of fire ants (Solenopsis invicta) or termites (Coptotermes formosanus) to create decision rules for a swarm of robots working together and organizing effectively to create a desired final excavated pattern.
First, a literature review of the behavioral rules of different types of insect colonies and the resulting structural patterns over the course of excavation was conducted. After identifying pertinent excavation laws, three different finite state machines were generated that relate to construction, search and rescue operations, and extraterrestrial exploration. After analyzing these finite state machines, it became apparent that they all shared a common controller. Then, agent-based NetLogo software was used to simulate a swarm of agents that run this controller, and a model for excavating behaviors and patterns was fit to the simulation data. This model predicts the tunnel shapes formed in the simulation as a function of the swarm size and a time delay, called the critical waiting period, in one of the state transitions. Thus, by controlling the individual agents' behavior, it was possible to control the structural outcomes of collective excavation in simulation.
To create an experimental testbed that could be used to physically implement the controller, a small foldable robotic platform was developed, and it's capabilities were tested in granular media. In order to characterize the granular media, force experiments were conducted and parameters were measured for resistive forces during an excavation cycle. The final experiment verified the robot's ability to engage in excavation and deposition, and to determine whether or not to begin the critical waiting period. This testbed can be expanded with multiple robots to conduct small-scale experiments on collective excavation, such as further exploring the effects of the critical waiting period on the resulting excavation pattern. In addition, investigating other factors like tuning digging efficiency or deposition proximity could help to transition the proposed bio-inspired swarm excavation controllers to implementation in real-world applications.
First, a literature review of the behavioral rules of different types of insect colonies and the resulting structural patterns over the course of excavation was conducted. After identifying pertinent excavation laws, three different finite state machines were generated that relate to construction, search and rescue operations, and extraterrestrial exploration. After analyzing these finite state machines, it became apparent that they all shared a common controller. Then, agent-based NetLogo software was used to simulate a swarm of agents that run this controller, and a model for excavating behaviors and patterns was fit to the simulation data. This model predicts the tunnel shapes formed in the simulation as a function of the swarm size and a time delay, called the critical waiting period, in one of the state transitions. Thus, by controlling the individual agents' behavior, it was possible to control the structural outcomes of collective excavation in simulation.
To create an experimental testbed that could be used to physically implement the controller, a small foldable robotic platform was developed, and it's capabilities were tested in granular media. In order to characterize the granular media, force experiments were conducted and parameters were measured for resistive forces during an excavation cycle. The final experiment verified the robot's ability to engage in excavation and deposition, and to determine whether or not to begin the critical waiting period. This testbed can be expanded with multiple robots to conduct small-scale experiments on collective excavation, such as further exploring the effects of the critical waiting period on the resulting excavation pattern. In addition, investigating other factors like tuning digging efficiency or deposition proximity could help to transition the proposed bio-inspired swarm excavation controllers to implementation in real-world applications.
ContributorsHaggerty, Zz Mae (Author) / Berman, Spring M (Thesis advisor) / Aukes, Daniel (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2018
Description
Stroke is a debilitating disorder and 75% of individuals with stroke (iwS) have upper extremity deficits. IwS are prescribed therapies to enhance upper-extremity mobility, but current most effective therapies have minimum requirements that the individuals with severe impairment do not meet. Thus, there is a need to enhance the therapies. Recent studies have shown that StartReact -the involuntary release of a planned movement, triggered by a startling stimulus (e.g., loud sound)- elicits faster and larger muscle activation in iwS compared to voluntary-initiated movement. However, StartReact has been only cursorily studied to date and there are some gaps in the StartReact knowledge. Previous studies have only evaluated StartReact on single-jointed movements in iwS, ignoring more functional tasks. IwS usually have abnormal flexor activity during extension tasks and abnormal muscle synergy especially during multi-jointed tasks; therefore, it is unknown 1) if more complex multi-jointed reach movements are susceptible to StartReact, and 2) if StartReact multi-jointed movements will be enhanced in the same way as single-jointed movements in iwS. In addition, previous studies showed that individuals with severe stroke, especially those with higher spasticity, experienced higher abnormal flexor muscle activation during StartReact trials. However, there is no study evaluating the impact of this elevated abnormal flexor activity on movement, muscle activation and muscle synergy alterations during voluntary-initiated movements after exposure to StartReact.
This dissertation evaluates StartReact and the voluntary trials before and after exposure to StartReact during a point-to-point multi-jointed reach task to three different targets covering a large workspace. The results show that multi-jointed reach tasks are susceptible to StartReact in iwS and the distance, muscle and movement onset speed, and muscle activations percentages and amplitude increase during StartReact trials. In addition, the distance, accuracy, muscle and movement onsets speeds, and muscle synergy similarity indices to the norm synergies increase during the voluntary-initiated trials after exposure to StartReact. Overall, this dissertation shows that exposure to StartReact did not impair voluntary-initiated movement and muscle synergy, but even improved them. Therefore, this study suggests that StartReact is safe for more investigations in training studies and therapy.
This dissertation evaluates StartReact and the voluntary trials before and after exposure to StartReact during a point-to-point multi-jointed reach task to three different targets covering a large workspace. The results show that multi-jointed reach tasks are susceptible to StartReact in iwS and the distance, muscle and movement onset speed, and muscle activations percentages and amplitude increase during StartReact trials. In addition, the distance, accuracy, muscle and movement onsets speeds, and muscle synergy similarity indices to the norm synergies increase during the voluntary-initiated trials after exposure to StartReact. Overall, this dissertation shows that exposure to StartReact did not impair voluntary-initiated movement and muscle synergy, but even improved them. Therefore, this study suggests that StartReact is safe for more investigations in training studies and therapy.
ContributorsRahimiTouranposhti, Marziye (Author) / Honeycutt, Claire F. (Thesis advisor) / Roh, Jinsook (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2020