This work analyzes human-in-the-loop robotic systems to determine where human input can be most beneficial to a collaborative task. This is accomplished by implementing a pick-and-place task using a human-in-the-loop robotic system and determining which segments of the task, when replaced by human guidance, provide the most improvement to overall task performance and require the least cognitive effort.
The first experiment entails implementing a pick and place task on a commercial robotic arm. Initially, we look at a pick-and-place task that is segmented into two main areas: coarse approach towards a goal object and fine pick motion. For the fine picking phase, we look at the importance of user guidance in terms of position and orientation of the end effector. Results from this initial experiment show that the most successful strategy for our human-in-the-loop system is the one in which the human specifies a general region for grasping, and the robotic system completes the remaining elements of the task. We extend this study to include a second experiment, utilizing a more complex robotic system and pick-and-place task to further analyze human impact in a human-in-the-loop system in a more realistic setting. In this experiment, we use a robotic system that utilizes an Xbox Kinect as a vision sensor, a more cluttered environment, and a pick-and-place task that we segment in a way similar to the first experiment.
Results from the second experiment indicate that allowing the user to make fine tuned adjustments to the position and orientation of the robotic hand can improve task success in high noise situations in which the autonomous robotic system might otherwise fail. The experimental setups and procedures used in this thesis can be generalized and used to guide similar analysis of human impact in other human-in-the-loop systems performing other tasks.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-5838 |
| Date | 01 January 2013 |
| Creators | Bringes, Christine Elizabeth |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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