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Robot Planning Based On Learned Affordances

This thesis studies how an autonomous robot can learn affordances from its interactions with the environment and use these affordances in planning. It is based on a new formalization of the concept which proposes that affordances are relations that pertain to the interactions of an agent with its environment. The robot interacts with environments containing different objects by executing its atomic actions and learns the different effects it can create, as well as the invariants of the environments that afford creating that effect with a certain action. This provides the robot with the ability to predict the consequences of its future interactions and to deliberatively plan action sequences to achieve a goal. The study shows that the concept of affordances provides a common framework for studying reactive control, deliberation and adaptation in autonomous robots. It also provides solutions to the major problems in robot planning, by grounding the planning operators in the low-level interactions of the robot.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12608551/index.pdf
Date01 August 2007
CreatorsCakmak, Maya
ContributorsSahin, Erol
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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