Mechanical Engineering ETDs
Publication Date
Summer 8-1-2022
Abstract
This research is motived by the study of dynamics, especially in experimentation and Structural Health Monitoring (SHM) methods. It is important that inspectors maintain awareness of test structures while observing sensor data and inputting control. Humans receive a large amount of information from vision, and this feedback is crucial to inform decision making. Human-computer interaction (HCI) provides valuable data and information but separates the human from reality as it is necessary to look away from the region of interest to view information on a separate device. Additionally, sensor data does not collect experiment safety, quality, and other contextual information of critical value to the operator. Safety, informed decisions, and control by engineers in the laboratory or field would be increased if they could maintain focus on their environment while evaluating the data their senses are not equipped to obtain (i.e., sensors and processing equipment). Furthermore, humans could advance robotic and machine manipulation if informed on real-time of the consequences of their decisions during human manipulation. To solve this problem, this research provides humans with Augmented Reality (AR) tools for engineering tasks. AR provides additional information to the AR user via head-mounted device (HMD), which allows the user to operate and observe the physical space without impedance. The two primary areas of focus in AR development in this MS thesis are visualization and control, where several applications are developed for specific use in engineering tasks. Elements of visualization and control are present in each of the applications. The primary application provides an interface for sensor feedback in AR. This inspires an AR interface for control of actuators in vibratory experimentation. The application is developed to plot sensor data in an interface complete with voltage, frequency, and duration controls for vibration generation. Implementing robots into cyber-physical systems for SHM promotes human capabilities that are improved by robot capabilities. Intuition often allows human workers to solve different tasks faster than robots, and when these human capabilities are coupled with the repeatability and endurance of robots then full potential can be realized. Two applications are developed for feedback and control of robotic arms in AR for the purpose of sensor deployment. The two arms are the Cyton Alpha 7-degree-of-freedom (DOF) arm and the Kinova Gen3 7DOF arm. This MS thesis also presents an AR application for an acoustic SHM method, deemed tap testing, which is used to detect signs of deterioration in structural surfaces through nondestructive means. The system is setup on a mobile robot titled Brutus, which is equipped with a sonar sensor to measure the distance between the robot and test surface. Experiments are conducted for verification of the developed applications, and the results of the reported experiments indicate that augmenting the information collected from sensors in real-time along with interfaces for control narrows the operator’s focus for more efficient and informed task conduction. This thesis considers the importance of human-centered framework where often experts in SHM prefer to be present to make decisions based on their own cognition, which can be coupled artificial intelligence and automation without solely depending on it. The research solves a problem with HCI where the operator experiences gaze distraction when attempting to monitor data and dynamic events. AR provides additional information to the AR user via HMD, which allows the user to continue to operate and observe the physical space without impedance. The results enable the research community to design, program, and examine new AR applications interfacing sensor feedback and control with real structures and environments.
Keywords
augmented reality, structural health monitoring, sensors, robots, experimentation
Degree Name
Mechanical Engineering
Level of Degree
Masters
Department Name
Mechanical Engineering
First Committee Member (Chair)
Dr. Fernando Moreu
Second Committee Member
Dr. Claus Danielson
Third Committee Member
Dr. Rafael Fierro
Document Type
Thesis
Recommended Citation
Wyckoff, Elijah. "Augmented Reality for Human Control of Engineering Tasks." (2022). https://digitalrepository.unm.edu/me_etds/216
