Robot Trust and Self-Confidence Role Arbitration Method for Physical Human-Robot Collaboration

Wang, Qiao

Robot Trust and Self-Confidence Role Arbitration Method for Physical Human-Robot Collaboration

Wang, Qiao

Permalink

Publication Type:: Thesis
Issue Date:: 2024

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download thesisAdobe PDF (14.73 MB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Wang, Qiao
dc.date.accessioned	2024-06-18T04:08:53Z
dc.date.available	2024-06-18T04:08:53Z
dc.date.issued	2024
dc.identifier.uri	http://hdl.handle.net/10453/179548
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	This thesis delves into physical Human-Robot Collaboration (pHRC), examining how humans and robots can cooperatively work within the same space to achieve common objectives. It highlights the essential role of trust in effective Human-Robot Interaction (HRI) and introduces a computational trust model that evaluates a robot's trust in its human partner based on factors safety, singularity avoidance, movement smoothness, and physical and cognitive performance. This model supports real-time adjustments in robot behavior to improve efficiency and teamwork. The study also proposes a trust-based role arbitration method that adjusts control between humans and robots dynamically, based on robot trust in human and robot self-confidence. Experiments involving humans validate these models, showing better collaboration, decreased workload for human co-workers, and improved satisfaction. Moreover, the thesis suggests the pairwise comparison method as a more accurate alternative compared to conventional rating scale method for assessing subjective impression during pHRC to enhance system design.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/179548/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2024 Qiao Wang
dc.rights	au.edu.uts.lib/cph
dc.title	Robot Trust and Self-Confidence Role Arbitration Method for Physical Human-Robot Collaboration	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

This thesis delves into physical Human-Robot Collaboration (pHRC), examining how humans and robots can cooperatively work within the same space to achieve common objectives. It highlights the essential role of trust in effective Human-Robot Interaction (HRI) and introduces a computational trust model that evaluates a robot's trust in its human partner based on factors safety, singularity avoidance, movement smoothness, and physical and cognitive performance. This model supports real-time adjustments in robot behavior to improve efficiency and teamwork. The study also proposes a trust-based role arbitration method that adjusts control between humans and robots dynamically, based on robot trust in human and robot self-confidence. Experiments involving humans validate these models, showing better collaboration, decreased workload for human co-workers, and improved satisfaction. Moreover, the thesis suggests the pairwise comparison method as a more accurate alternative compared to conventional rating scale method for assessing subjective impression during pHRC to enhance system design.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/179548