Doctoral Thesis
Assigned responsibility: An architecture for mixed control robot teleoperation
Doctor of Philosophy (PhD), Murdoch University
2016
Abstract
Teleoperated robots are well suited to many tasks involving actions in hazardous environments due to their resilience and variety in sensory capabilities, size, tooling, and instrument-carrying capacity. Teleoperation can be achieved through a variety of control modes, ranging from direct human control of all systems to fully automated control. Some teleoperation systems use a range of these modes and encourage actively switching between them to suit the situation at hand. Most of these systems choose a reactive approach, relying on the controller (human or automated) to respond to changes in the task by switching appropriately.
The research presented in this thesis focuses on an unexplored gap in the spectrum of possible strategies for this mode switching. In situations where the environment is known and/or predictable, pre-planning these control changes could relieve robot operators of this additional task. Such a strategy provides a clear division of labour between the automation and the human operator(s) before the job even begins, allowing for individual responsibilities to be known ahead of time, thus limiting confusion and allowing breaks to be planned, for example.
This thesis proposes an assigned responsibility strategy, with an architecture supporting these pre-planned changes. A practical implementation of assigned responsibility is produced. This is evaluated through engineering tests and a usability study, demonstrating the viability of this approach as well as offering insight into its potential applications.
Details
- Title
- Assigned responsibility: An architecture for mixed control robot teleoperation
- Authors/Creators
- Nicolas Small
- Contributors
- Graham Mann (Supervisor)Kevin Lee (Supervisor)
- Awarding Institution
- Murdoch University; Doctor of Philosophy (PhD)
- Identifiers
- 991005541697507891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Doctoral Thesis
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