Theses and Dissertations

Date of Award

12-2023

Document Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Engineering Management

First Advisor

Douglas Timmer

Second Advisor

Zhaohui Geng

Third Advisor

Jianzhi Li

Abstract

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This study explores the integration of collaborative robotics (cobots) with eye tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in 3D scanning, particularly in the capture of functionally critical areas, and to provide a detailed description of regions with complex geometric features. The study develops a framework where the scanning path of the robot-carried scanner is partially guided by the eye-tracking data, i.e., the calibrated gaze tracking, to improve the automated 3D scanning process. This framework provides an innovative integration of human gaze movement with automatic robot path planning, providing a new way of human-autonomy teaming. Case studies are presented to present and validate the proposed framework to automatically improve the 3D point cloud collection process, specifically in the areas that usually require human manual intervention to capture details.

Comments

Copyright 2023 Sachithra H. Karunathilake. All Rights Reserved.

https://go.openathens.net/redirector/utrgv.edu?url=https://www.proquest.com/pqdtglobal1/dissertations-theses/gaze-tracking-embedded-collaborative-robots/docview/2928421017/sem-2?accountid=7119

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