SHI, CHENJIE (2021) Theory of Self-maintaining Robots. MPhil thesis, University of Sheffield.
Abstract
This thesis proposes a theory for robotic systems that can be fully
self-maintaining. The presented design principles focus on functional survival of
the robots over long periods of time without human maintenance.
Self-maintaining semi-autonomous mobile robots are in great demand in nuclear
disposal sites from where their removal for maintenance is undesirable due to
their radioactive contamination. Similar are requirements for robots in various
defence tasks or space missions. For optimal design, modular solutions are
balanced against capabilities to replace smaller components in a robot by itself or
by help from another robot. Modules are proposed for the basic platform, which
enable self-maintenance within a team of robots helping each other. The primary
method of self-maintenance is replacement of malfunctioning modules or
components by the robots themselves. Replacement necessitates a robot team’s
ability to diagnose and replace malfunctioning modules as needed. Due to their
design, these robots still remain manually re-configurable if opportunity arises for
human intervention. A system reliability model is developed to
describe the new theory. Depending on the system reliability model,
the redundancy allocation problem is presented and solved by a multi objective
algorithm.
Finally, the thesis introduces the self-maintaining process and transfers it to a multi robot task allocation problem with a solution by genetic algorithm.
Metadata
Supervisors: | Veres, Sandor |
---|---|
Keywords: | Robot Intelligence, Self-maintenance, Reliability theory, Redundancy allocation problem, Multi robots task allocation |
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Mr CHENJIE SHI |
Date Deposited: | 13 Dec 2021 09:27 |
Last Modified: | 13 Dec 2021 09:27 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:29885 |
Download
Final eThesis - complete (pdf)
Filename: CSHI_Thesis.pdf
Description: Thesis
Licence:
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 2.5 License
Export
Statistics
You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.