Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Polygerinos, Panagiotis
Description
The interaction between humans and robots has become an important area of research as the diversity of robotic applications has grown. The cooperation of a human and robot to achieve a goal is an important area within the physical human-robot interaction (pHRI) field. The expansion of this field is toward moving robotics into applications in unstructured environments. When humans cooperate with each other, often there are leader and follower roles. These roles may change during the task. This creates a need for the robotic system to be able to exchange roles with the human during a cooperative task. The unstructured nature of the new applications in the field creates a need for robotic systems to be able to interact in six degrees of freedom (DOF). Moreover, in these unstructured environments, the robotic system will have incomplete information. This means that it will sometimes perform an incorrect action and control methods need to be able to correct for this. However, the most compelling applications for robotics are where they have capabilities that the human does not, which also creates the need for robotic systems to be able to correct human action when it detects an error. Activity in the brain precedes human action. Utilizing this activity in the brain can classify the type of interaction desired by the human. For this dissertation, the cooperation between humans and robots is improved in two main areas. First, the ability for electroencephalogram (EEG) to determine the desired cooperation role with a human is demonstrated with a correct classification rate of 65%. Second, a robotic controller is developed to allow the human and robot to cooperate in six DOF with asymmetric role exchange. This system allowed human-robot cooperation to perform a cooperative task at 100% correct rate. High, medium, and low levels of robotic automation are shown to affect performance, with the human making the greatest numbers of errors when the robotic system has a medium level of automation.
ContributorsWhitsell, Bryan Douglas (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Polygerinos, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2017
Description
The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation therapies focus on strengthening motor skills, such as grasping, employ multiple objects of varying stiffness and devices that are bulky, costly, and have limited range of stiffness due to the rigid mechanisms employed in their variable stiffness actuators. This research project presents a portable cost-effective soft robotic haptic device with a broad stiffness range that is adjustable and can be utilized in both clinical and home settings. The device eliminates the need for multiple objects by employing a pneumatic soft structure made with highly compliant materials that act as the actuator as well as the structure of the haptic interface. It is made with interchangeable soft elastomeric sleeves that can be customized to include materials of varying stiffness to increase or decrease the stiffness range. The device is fabricated using existing 3D printing technologies, and polymer molding and casting techniques, thus keeping the cost low and throughput high. The haptic interface is linked to either an open-loop system that allows for an increased pressure during usage or closed-loop system that provides pressure regulation in accordance with the stiffness the user specifies. A preliminary evaluation is performed to characterize the effective controllable region of variance in stiffness. Results indicate that the region of controllable stiffness was in the center of the device, where the stiffness appeared to plateau with each increase in pressure. The two control systems are tested to derive relationships between internal pressure, grasping force exertion on the surface, and displacement using multiple probing points on the haptic device. Additional quantitative evaluation is performed with study participants and juxtaposed to a qualitative analysis to ensure adequate perception in compliance variance. Finally, a qualitative evaluation showed that greater than 60% of the trials resulted in the correct perception of stiffness in the haptic device.
ContributorsSebastian, Frederick (Author) / Polygerinos, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Fu, Qiushi (Committee member) / Arizona State University (Publisher)
Created2018