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Integrating Context Inference and Planning in a Network Robot System
Örebro University, School of Science and Technology, Örebro University, Sweden.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Context Inference and Planning are becoming more and more valuable in robot

oriented technology and several artificial intelligence techniques exist for solving

both context inference and planning problems. However, not many combinations

of context inference and planning solving have been tried and evaluated

as well as comparison between these combinations.

This thesis aims to compare two different algorithms, using two different approaches

to the problems of context inference and planning. The algorithms

studied are Graphplan, which is a classical planning approach to context inference

and planning, and SAM, a framework created by the Örebro University,

that uses a temporal constraint-based approach. It will also evaluate the expressiveness

of these two algorithms applied to the system. To do so an implementation

and test of the two approaches is evaluated on a real robot system.

This evaluation will show that SAM is much more expressive in terms of domain

definition than Graphplan and that reasoning about temporal constraints

could become crucial for achieving a system that can succesfully recognize context

inference and plan accordingly. The decision on whether to apply one or

another is just depending on the kind of system the user needs. If temporal constraints

are mandatory, then SAM is the choice to make; in case the only thing

the system needs is a fast algorithm able to always find a plan, if it exists, then

Graphplan is a better choice.

Place, publisher, year, edition, pages
2015. , 78 p.
National Category
Computer Science
URN: urn:nbn:se:oru:diva-45441OAI: diva2:844157
Subject / course
Computer Engineering
Available from: 2015-08-04 Created: 2015-08-04 Last updated: 2015-08-04Bibliographically approved

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School of Science and Technology, Örebro University, Sweden
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