Learning and Using Context on a Humanoid Robot Using Latent Dirichlet Allocation

Date

2014-10-16

Author

Celikkanat, Hande
Orhan, Guner
Pugeault, Nicolas
Guerin, Frank
Şahin, Erol
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

225
views

0
downloads

In this work, we model context in terms of a set of concepts grounded in a robot's sensorimotor interactions with the environment. For this end, we treat context as a latent variable in Latent Dirichlet Allocation, which is widely used in computational linguistics for modeling topics in texts. The flexibility of our approach allows many-to-many relationships between objects and contexts, as well as between scenes and contexts. We use a concept web representation of the perceptions of the robot as a basis for context analysis. The detected contexts of the scene can be used for several cognitive problems. Our results demonstrate that the robot can use learned contexts to improve object recognition and planning.

Subject Keywords

Scene

URI

https://hdl.handle.net/11511/53423

Conference Name

4th Joint IEEE International Conferences on Development and Learning and Epigenetic Robotics (IEEE ICDL-Epirob)

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Learning Context on a Humanoid Robot using Incremental Latent Dirichlet Allocation Çelikkanat, Hande; Orhan, Guner; Pugeault, Nicolas; Guerin, Frank; Şahin, Erol; Kalkan, Sinan (Institute of Electrical and Electronics Engineers (IEEE), 2016-03-01) In this paper, we formalize and model context in terms of a set of concepts grounded in the sensorimotor interactions of a robot. The concepts are modeled as a web using Markov Random Field (MRF), inspired from the concept web hypothesis for representing concepts in humans. On this concept web, we treat context as a latent variable of Latent Dirichlet Allocation (LDA), which is a widely-used method in computational linguistics for modeling topics in texts. We extend the standard LDA method in order to make ...
An active fuzzy object-oriented database approach Bostan-Korpeoglu, B; Yazıcı, Adnan (2004-07-29) Knowledge intensive applications require an intelligent environment which can perform deductions due to user queries or events that occur inside or outside of the environment. In this study, we propose a fuzzy active object-oriented database for modelling knowledge intensive applications. Our approach integrates fuzzy, active and deductive rules with database objects, so that the system gains intelligent behaviour, which provides objects to perceive dynamic occurences and answer user queries. In this way, o...
INTEGRATION OF 2D IMAGES AND RANGE DATA FOR OBJECT SEGMENTATION AND RECOGNITION Bayramoglu, Neslihan; Akman, Oytun; Alatan, Abdullah Aydın; Jonker, Pieter (2009-09-11) In the field of vision based robot actuation, in order to manipulate objects in an environment, background separation and object selection a re fundamental tasks that should be carried out in a fast and efficient way. In this paper, we propose a method to segment possible object locations in the scene and recognize them via local-point based representation. Exploiting the resulting 3D structure of the scene via a time-of-flight camera, background regions are eliminated with the assumption that the objects a...
Modeling of biochemical networks via classification and regression tree methods Seçilmiş, Deniz; Purutçuoğlu Gazi, Vilda (Springer, 2018-08-01) In the description of biological networks, a number of modeling approaches has been suggested based on different assumptions. The major problems in these models and their associated inference approaches are the complexity of biological systems, resulting in high number of model parameters, few observations from each variable in the system, their sparse structures, and high correlation between model parameters. From recent studies, it has been seen that the nonparametric methods can ameliorate these challeng...
Learning affordances for categorizing objects and their properties Dag̃, Nilgün; Atil, Ilkay; Kalkan, Sinan; Şahin, Erol (2010-11-18) In this paper, we demonstrate that simple interactions with objects in the environment leads to a manifestation of the perceptual properties of objects. This is achieved by deriving a condensed representation of the effects of actions (called effect prototypes in the paper), and investigating the relevance between perceptual features extracted from the objects and the actions that can be applied to them. With this at hand, we show that the agent can categorize (i.e., partition) its raw sensory perceptual fe...

Citation Formats

H. Celikkanat, G. Orhan, N. Pugeault, F. Guerin, E. Şahin, and S. Kalkan, “Learning and Using Context on a Humanoid Robot Using Latent Dirichlet Allocation,” presented at the 4th Joint IEEE International Conferences on Development and Learning and Epigenetic Robotics (IEEE ICDL-Epirob), Genoa, ITALY, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53423.