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Dissertation/Thesis Abstract

Incorporating Haptics in a Human-robot Collaborative Manufacturing Process
by Martinez, Joaquin, M.S., California State University, Long Beach, 2019, 44; 22585317
Abstract (Summary)

As manufacturing and robotics develop, automation and robotic integration is becoming increasingly prevalent in manufacturing processes. Humans are still essential parts of most manufacturing processes due to the complexity and specialization of many manufacturing processes. As such, systems and methods need to be developed to support and advance robot-human collaboration and allow for the expansion of robotic integration into previously human only manufacturing processes. This thesis aims to explore the utility of several protocols for robotic-human communication - visual, auditory, and haptic cues, and to investigate the viability of haptic communication as a method to support robot-human collaboration. A simulated manufacturing task was designed and components were built to facilitate two experiments to test two hypotheses: 1) Humans respond faster to haptic cues than they do to visual or auditory cues and 2) Humans complete tasks more quickly when provided with assistance in the form of haptic cues than they do when provided with assistance in the form of either visual or auditory cues. As a group subjects performed better on all tasks when provided with haptic cues (EI M = 2.36, SD = 0.3592; EII M = 80.43, SD = 3.8039) than they did when provided with either visual (EI M = 2.47, SD = 0.3753; EII M = 82.85, SD = 5.9517) or auditory (EI M = 2.67, SD = 0.4002; EII M = 81.91, SD = 4.9043) cues. The differences in response and task completion times were found to be statistically significant at the .05 level. The findings of this thesis project demonstrate the efficacy of the use of haptics for enhancing human-robot communication.

Indexing (document details)
Advisor: Demircan, Emel
Commitee: Shankar, Praveen, Khoo, I-Hung
School: California State University, Long Beach
Department: Mechanical and Aerospace Engineering
School Location: United States -- California
Source: MAI 81/4(E), Masters Abstracts International
Subjects: Engineering
Publication Number: 22585317
ISBN: 9781687953865
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