Perception and reasoning for the automatic configuration of task and motion planning problems
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/356803
Tipus de documentProjecte Final de Màster Oficial
Data2021-10-11
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
This thesis proposes a framework for configuring Task Planning Problems flexibly in an automatic manner using two main modules which are the Perception Module and the Reasoning Module. In order to automatize the overall process, initially, a knowledge layer is generated manually, in which the information regarding the environment is stored using ontologies, whereas the environmental state where the task is taking place is observed with the help of the Perception Module. The knowledge layer is then reasoned within the Reasoner Module in order to automatically configure task planning problems by filling Planning Domain Definition Language (PDDL) [1] files. During this reasoning process, the information retrieved from the Perception Module is used. In this paper, both of these modules mentioned above are explained in detail before providing the results separately for each module. Then, in addition to individual results, a scenario is created within a lab environment to test the overall system including both modules. Furthermore, alternative areas where the Reasoning Module implementation can be benefited from is also discussed
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
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fatma-nur-arabaci-tfm.pdf | 14,00Mb | Visualitza/Obre |