Numerous diseases and injuries can limit a person's ability to perform everyday tasks -- things like getting dressed, bathing, and eating. Anything that requires physical activity can be affected; even simple things like turning on the lights can become difficult or impossible. Until recently, the only way for a person...
This dissertation focuses on personal privacy in human-robot interaction, which we call "privacy-sensitive robotics." Our understanding of "privacy" is very broad, including not just information privacy but also physical, psychological, and social privacy. We begin by surveying the scholarly literature on privacy and talking about why it applies to interactions...
State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
The purpose of this investigation was to examine the influence of selected historical, fiscal, and organizational factors on enrollment patterns in Oregon Community Colleges during the academic years 1978-79, 1981-82, and 1984-85. Oregon was selected insofar as it is one of the few remaining states which observes the principle of...
This dissertation presents novel, field-activated smart material systems for the actuation and control of autonomous robots. Smart materials, a type of material whose properties can be changed with an external stimuli, represent a promising direction to expand upon existing robotic control and actuation methods, particularly in the sub-fields of soft...
The last decade has seen a drastic interest in microgrids throughout the world. Even though this trend might seem to be just another technological solution in the energy sector, it is a part of a greater transition from a centralized energy system to a more decentralized one. However, unlike most...
Multiagent approaches are well suited to designing autonomous solutions for systems that feature complex interactions between many individuals such as in autonomous traffic systems and multi-robot exploration systems. However, creating autonomous agents that function effectively in these systems is a challenging task. In these complex environments, agents need informative reward...
Multi-robot teams offer promising solutions for many long term deployments in remote and dangerous domains, such as extraterrestrial or underseas exploration. However, long term deployments present many problems preventing robot teams from operating effectively. Learning over long time scales is makes it difficult to assign credit to robots' actions, as...
Deep learning has recently revolutionized robot perception in many canonical robotic applications, such as autonomous driving. However, a similar transformation has yet to occur in more harsh environments including underwater and underground. This is due in part to the difficulty in deploying robots in these environments, which lack large real...
Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...