The development of test action bank for active robot learning

2.50
Hdl Handle:
http://hdl.handle.net/10547/344359
Title:
The development of test action bank for active robot learning
Authors:
Cao, Tao
Abstract:
In the rapidly expanding service robotics research area, interactions between robots and humans become increasingly cornmon as more and more jobs will require cooperation between the robots and their human users. It is important to address cooperation between a robot and its user. ARL is a promising approach which facilitates a robot to develop high-order beliefs by actively performing test actions in order to obtain its user's intention from his responses to the actions. Test actions are crucial to ARL. This study carried out primary research on developing a Test Action Bank (TAB) to provide test actions for ARL. In this study, a verb-based task classifier was developed to extract tasks from user's commands. Taught tasks and their corresponding test actions were proposed and stored in database to establish the TAB. A backward test actions retrieval method was used to locate a task in a task tree and retrieve its test actions from TAB. A simulation environment was set up with a service robot model and a user model to test TAB and demonstrate some test actions. Simulations were also perfonned in this study, the simulation results proved TAB can successfully provide test actions according to different tasks and the proposed service robot model can demonstrate test actions.
Citation:
Cao, T. (2009_ 'The development of test action bank for active robot learning'. MSc by research thesis. University of Bedfordshire.
Publisher:
University of Bedfordshire
Issue Date:
Nov-2009
URI:
http://hdl.handle.net/10547/344359
Type:
Thesis or dissertation
Language:
en
Description:
A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Master of Science by research
Appears in Collections:
Masters e-theses

Full metadata record

DC FieldValue Language
dc.contributor.authorCao, Taoen
dc.date.accessioned2015-02-10T13:00:05Z-
dc.date.available2015-02-10T13:00:05Z-
dc.date.issued2009-11-
dc.identifier.citationCao, T. (2009_ 'The development of test action bank for active robot learning'. MSc by research thesis. University of Bedfordshire.en
dc.identifier.urihttp://hdl.handle.net/10547/344359-
dc.descriptionA thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Master of Science by researchen
dc.description.abstractIn the rapidly expanding service robotics research area, interactions between robots and humans become increasingly cornmon as more and more jobs will require cooperation between the robots and their human users. It is important to address cooperation between a robot and its user. ARL is a promising approach which facilitates a robot to develop high-order beliefs by actively performing test actions in order to obtain its user's intention from his responses to the actions. Test actions are crucial to ARL. This study carried out primary research on developing a Test Action Bank (TAB) to provide test actions for ARL. In this study, a verb-based task classifier was developed to extract tasks from user's commands. Taught tasks and their corresponding test actions were proposed and stored in database to establish the TAB. A backward test actions retrieval method was used to locate a task in a task tree and retrieve its test actions from TAB. A simulation environment was set up with a service robot model and a user model to test TAB and demonstrate some test actions. Simulations were also perfonned in this study, the simulation results proved TAB can successfully provide test actions according to different tasks and the proposed service robot model can demonstrate test actions.en
dc.language.isoenen
dc.publisherUniversity of Bedfordshireen
dc.subjectH671 Roboticsen
dc.subjectroboticsen
dc.subjectactive robot learningen
dc.subjecttest action banken
dc.subjecthuman-robot interaction;en
dc.titleThe development of test action bank for active robot learningen
dc.typeThesis or dissertationen
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