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Filtering by: Committee Member Smart, William D. Contributor advisor sim Hollinger, Geoffrey A.

Planning Under Uncertainty for Unmanned Aerial Vehicles

Creator:

Skeele, Ryan

Abstract:

Unmanned aerial vehicle (UAV) technology has grown out of traditional research and military applications and has captivated the commercial and consumer markets, showing the ability to perform a spectrum of autonomous functions. This technology has the capability of saving lives in search and rescue, fighting wildfires in environmental monitoring, and...

Resource Type:

Masters Thesis

Full Text:

data. In all cases, RAGS is shown to reduce the probability of executing high-cost paths over A*, D
Augmented Deep Learning Techniques for Robotic State Estimation

Creator:

Nicolai, Austin L.

Abstract:

While robotic systems may have once been relegated to structured environments and automation style tasks, in recent years these boundaries have begun to erode. As robots begin to operate in largely unstructured environments, it becomes more difficult for them to effectively interpret their surroundings. As sensor technology improves, the amount...

Resource Type:

Dissertation

Full Text:

continued support and mentorship during my time at OSU. I would also like to thank Drs. William Smart
Efficiently Learning Human Preferences for Robot Autonomy

Creator:

Somers, Thane N.

Abstract:

Human-robot teams are invaluable for mapping unknown environments, exploring difficult-to-reach areas, and manipulating inaccessible equipment. However, guiding autonomous robots requires dealing with these dynamic domains while synthesizing a significant amount of data and balancing competing objectives. Current mission planning methods often involve manually specifying low-level parameters of the mission, such...

Resource Type:

Masters Thesis

Full Text:

of the members of my committee—Dr. Bill Smart, Dr. Julie Adams, Dr. Alan Fern, and Dr. Bogdan