Award Date
12-1-2021
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mechanical Engineering
First Committee Member
Paul Oh
Second Committee Member
Woosoon Yim
Third Committee Member
Mohamed Trabia
Fourth Committee Member
Georg Mauer
Fifth Committee Member
Jin Ouk Choi
Number of Pages
132
Abstract
Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth be known as dexterous aerial manipulation.
Our recent work integrated the worker’s experience into aerial manipulation using haptic technology. The net effect was such a system could enable the worker to leverage drones and complete tasks while utilizing haptics on the task site remotely. However, the tasks were completed within the operator’s line-of-sight. Until now, immersive AR/VR frameworks has rarely been integrated in aerial manipulation. Yet, such a framework allows the drones to embody and transport the operator’s senses, actions, and presence to a remote location in real-time. As a result, the operator can both physically interact with the environment and socially interact with actual workers on the worksite.
This dissertation presents a human-embodied drone interface for dexterous aerial manipulation. Using VR/AR technology, the interface allows the operator to leverage their intelligence to collaboratively perform desired tasks anytime, anywhere with a drone that possesses great dexterity.
Keywords
aerial manipulation; aerial vehicles; AR/VR; embodiment; robotics
Disciplines
Artificial Intelligence and Robotics | Robotics
File Format
File Size
27800 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Kim, Dongbin, "A Human-Embodied Drone for Dexterous Aerial Manipulation" (2021). UNLV Theses, Dissertations, Professional Papers, and Capstones. 4298.
http://dx.doi.org/10.34917/28340348
Rights
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