Engineering Commons^™

A Brain Robot Interface For Autonomous Activities Of Daily Living Tasks, Don Indika Upashantha Pathirage

USF Tampa Graduate Theses and Dissertations

There have been substantial improvements in the area of rehabilitation robotics in the recent past. However, these advances are inaccessible to a large number of people with disabilities who are in most need of such assistance. This group includes people who are in a severely paralyzed state, that they are completely "locked-in" in their own bodies. Such persons usually retain full cognitive abilities, but have no voluntary muscle control.

For these persons, a Brain Computer Interface (BCI) is often the only way to communicate with the outside world and/or control an assistive device. One major drawback to BCI devices is …

A Multi-Case Study Of Student Interactions With Educational Robots And Impact On Science, Technology, Engineering, And Math (Stem) Learning And Attitudes, Stephanie Holmquist

USF Tampa Graduate Theses and Dissertations

The demand for STEM trained workers continues to increase not only in the United States, but globally. Reports have indicated that the United States is not doing a good job encouraging students to pursue STEM oriented degrees. In particular, it has become increasingly important to emphasize STEM connections at an early level in order to encourage student career exploration as they continue their education. Educational robots represent a unique alternative to traditional methods, especially at the elementary level. Considering the use of educational robots have largely been ignored at this level, the purpose of this study was to describe the …

Scene-Dependent Human Intention Recognition For An Assistive Robotic System, Kester Duncan

USF Tampa Graduate Theses and Dissertations

In order for assistive robots to collaborate effectively with humans for completing everyday tasks, they must be endowed with the ability to effectively perceive scenes and more importantly, recognize human intentions. As a result, we present in this dissertation a novel scene-dependent human-robot collaborative system capable of recognizing and learning human intentions based on scene objects, the actions that can be performed on them, and human interaction history. The aim of this system is to reduce the amount of human interactions necessary for communicating tasks to a robot. Accordingly, the system is partitioned into scene understanding and intention recognition modules. …