A Probabilistic Concept Web on a Humanoid Robot

Date

2015-06-01

Author

Çelikkanat, Hande
Orhan, Guner
Kalkan, Sinan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

173
views

0
downloads

It is now widely accepted that concepts and conceptualization are key elements towards achieving cognition on a humanoid robot. An important problem on this path is the grounded representation of individual concepts and the relationships between them. In this article, we propose a probabilistic method based on Markov Random Fields to model a concept web on a humanoid robot where individual concepts and the relations between them are captured. In this web, each individual concept is represented using a prototype-based conceptualization method that we proposed in our earlier work. Relations between concepts are linked to the cooccurrences of concepts in interactions. By conveying input from perception, action, and language, the concept web forms rich, structured, grounded information about objects, their affordances, words, etc. We demonstrate that, given an interaction, a word, or the perceptual information from an object, the corresponding concepts in the web are activated, much the same way as they are in humans. Moreover, we show that the robot can use these activations in its concept web for several tasks to disambiguate its understanding of the scene.

Subject Keywords

Concepts, Conceptualization, Concept web, Markov Random Fields

URI

https://hdl.handle.net/11511/36205

Journal

IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT

DOI

https://doi.org/10.1109/tamd.2015.2418678

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Integrating Spatial Concepts into a Probabilistic Concept Web Celikkanat, Hande; Şahin, Erol; Kalkan, Sinan (2015-07-31) In this paper, we study the learning and representation of grounded spatial concepts in a probabilistic concept web that connects them with other noun, adjective, and verb concepts. Specifically, we focus on the prepositional spatial concepts, such as "on", "below", "left", "right", "in front of" and "behind". In our prior work (Celikkanat et al., 2015), inspired from the distributed highly-connected conceptual representation in human brain, we proposed using Markov Random Field for modeling a concept web o...
A Grounded and contextualized web of concepts on a humanoid robot Çelikkanat, Hande; Kalkan, Sinan; Şahin, Erol; Department of Computer Engineering (2015) In this thesis, we propose a formalization for a densely connected representation of concepts and their contexts on a humanoid robot platform. Although concepts have been studied implicitly and explicitly in numerous studies before,our study is unique in placing the relatedness of concepts to the center: We hypothesize that a concept is fully meaningful only when considered in relation to the other concepts. Thus, we propose a novel densely connected web of concepts, and show how utilizing the relatedness o...
Estimating and reshaping human intention via human robot interaction DURDU, AKİF; Erkmen, İsmet; Erkmen, Aydan Müşerref (2016-01-01) Human robot interaction (HRI) is studied in two important research areas, intention estimation and intention reshaping. Although there are many studies in the literature that define human intention, new research examines the reshaping of human intentions by using robots in HRI. In this paper, 2 different robot movements are tested in a real environment in order to reshape current human intention. The hidden Markov model (HMM) is used to estimate human intention in our intelligent robotic system. The algorit...
A control system using behaviour hierarchies and neuro-fuzzy approach Arslan, Dilek; Alpaslan, Ferda Nur; Department of Computer Engineering (2005) In agent based systems, especially in autonomous mobile robots, modelling the environment and its changes is a source of problems. It is not always possible to effectively model the uncertainity and the dynamic changes in complex, real-world domains. Control systems must be robust to changes and must be able to handle these uncertainties to overcome this problem. In this study, a reactive behaviour based agent control system is modelled and implemented. The control system is tested in a navigation task usin...
A control system using behavior hierarchies and neuro-fuzyy approach Arslan, Didem; Alpaslan, Ferda Nur (null; 2005-09-14) In agent-based systems, especially in autonomous mobile robots, modelling the environment and its changes is a source of problems. It is not always possible to effectively model the uncertainty and the dynamic changes in complex, real-world domains. Control systems must be robust to changes and must be able to handle the uncertainties to overcome this problem. In this study, a reactive behaviour based agent control system is modelled and implemented. The control system is tested in a navigation task using a...

Citation Formats

H. Çelikkanat, G. Orhan, and S. Kalkan, “A Probabilistic Concept Web on a Humanoid Robot,” IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT, pp. 92–106, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36205.