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A Teleological Approach to Robot Programming by Demonstration

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dc.contributor.advisorRoderic A. Grupen
dc.contributor.advisorOliver Brock
dc.contributor.advisorAndrew H. Fagg
dc.contributor.authorSweeney, John Douglas
dc.contributor.departmentUniversity of Massachusetts Amherst
dc.date2023-09-23T03:36:31.000
dc.date.accessioned2024-04-26T19:48:29Z
dc.date.available2024-04-26T19:48:29Z
dc.date.issued2011-02-01
dc.description.abstractThis dissertation presents an approach to robot programming by demonstration based on two key concepts: demonstrator intent is the most meaningful signal that the robot can observe, and the robot should have a basic level of behavioral competency from which to interpret observed actions. Intent is a teleological, robust teaching signal invariant to many common sources of noise in training. The robot can use the knowledge encapsulated in sensorimotor schemas to interpret the demonstration. Furthermore, knowledge gained in prior demonstrations can be applied to future sessions. I argue that programming by demonstration be organized into declarative and pro-cedural components. The declarative component represents a reusable outline of underlying behavior that can be applied to many different contexts. The procedural component represents the dynamic portion of the task that is based on features observed at run time. I describe how statistical models, and Bayesian methods in particular, can be used to model these components. These models have many features that are beneficial for learning in this domain, such as tolerance for uncertainty, and the ability to incorporate prior knowledge into inferences. I demonstrate this architecture through experiments on a bimanual humanoid robot using tasks from the pick and place domain. Additionally, I develop and experimentally validate a model for generating grasp candidates using visual features that is learned from demonstration data. This model is especially useful in the context of pick and place tasks.
dc.description.degreeDoctor of Philosophy (PhD)
dc.description.departmentComputer Science
dc.identifier.doihttps://doi.org/10.7275/1929768
dc.identifier.urihttps://hdl.handle.net/20.500.14394/38788
dc.relation.urlhttps://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1352&context=open_access_dissertations&unstamped=1
dc.source.statuspublished
dc.subjectdemonstration
dc.subjectgrasping
dc.subjectprogramming
dc.subjectstatistical models
dc.subjectComputer Sciences
dc.titleA Teleological Approach to Robot Programming by Demonstration
dc.typedissertation
dc.typearticle
dc.typedissertation
digcom.contributor.authorSweeney, John Douglas
digcom.identifieropen_access_dissertations/351
digcom.identifier.contextkey1929768
digcom.identifier.submissionpathopen_access_dissertations/351
dspace.entity.typePublication
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