Journal Papers by Gibran Fuentes-Pineda
International Journal of Advanced Robotic Systems, 2013
In this paper we present SitLog: a declarative situation-oriented logical language for programmin... more In this paper we present SitLog: a declarative situation-oriented logical language for programming situated service robot tasks. The formalism is task and domain independent, and can be used in a wide variety of settings. SitLog can also be seen as a behaviour engineering specification and interpretation formalism to support action selection by autonomous agents during the execution of complex tasks. The language combines the recursive transition network formalism, extended with functions to express dynamic and contextualized task structures, with a functional language to express control and content information. The SitLog interpreter is written in Prolog and SitLog’s programs follow closely the Prolog notation, permitting the declarative specification and direct interpretation of complex applications in a modular and compact form.We discuss the structure and representation of service robot tasks in practical settings and how these can be expressed in SitLog. The present framework has been tested in the service robot Golem-II+ using the specification and programming of the typical tasks which require completion in the RoboCup@Home Competition.
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Papers by Gibran Fuentes-Pineda
International Journal of Advanced Robotic Systems, 2015
Sound source localization is important in human interaction, such as in locating the origin of lo... more Sound source localization is important in human interaction, such as in locating the origin of long-distance calls or facing other humans while in a conversation. It is of interest to apply such functionality to the core of human-robot interaction (HRI) and investigate its benefits, if any. In this paper, we propose three strategies for how to integrate the functionality of multiple directions-of-arrival (multi-DOA) estimation with a common scenario, in which the robot acts as a waiter while applying audio source localization. The proposed strategies are: a) the robot locates calls from users at a relatively long distance; b) the robot faces the user when taking the order; and c) the robot announces whether the acoustic environment is not conducive to understanding a speech command (mainly where more than one user speaks at once). It was seen that users react favourably to the functionality, and that it even has a noticeable influence on the success of the interaction. http://www.intechopen.com/books/international_journal_of_advanced_robotic_systems/integration-of-the-multi-doa-estimation-functionality-to-human-robot-interaction
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Lecture Notes in Computer Science, 2009
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2010 20th International Conference on Pattern Recognition, 2010
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IEICE Transactions on Information and Systems, 2011
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Drafts by Gibran Fuentes-Pineda
The task of discovering topics in text corpora has been dominated by Latent Dirichlet Allocation ... more The task of discovering topics in text corpora has been dominated by Latent Dirichlet Allocation and other Topic Models for over a decade. In order to apply these approaches to massive text corpora, the vocabulary needs to be reduced considerably and large computer clusters and/or GPUs are typically required. Moreover , the number of topics must be provided beforehand but this depends on the corpus characteristics and it is often difficult to estimate, especially for massive text corpora. Unfortunately, both topic quality and time complexity are sensitive to this choice. This paper describes an alternative approach to discover topics based on Min-Hashing, which can handle massive text corpora and large vocabularies using modest computer hardware and does not require to fix the number of topics in advance. The basic idea is to generate multiple random partitions of the corpus vocabulary to find sets of highly co-occurring words, which are then clustered to produce the final topics. In contrast to probabilistic topic models where topics are distributions over the complete vocabulary, the topics discovered by the proposed approach are sets of highly co-occurring words. Interestingly, these topics underlie various thematics with different levels of granularity. An extensive qualitative and quantitative evaluation using the 20 Newsgroups (18K), Reuters (800K), Spanish Wikipedia (1M), and English Wikipedia (5M) corpora shows that the proposed approach is able to consistently discover meaningful and coherent topics. Remarkably, the time complexity of the proposed approach is linear with respect to corpus and vocabulary size; a non-parallel implementation was able to discover topics from the entire English edition of Wikipedia with over 5 million documents and 1 million words in less than 7 hours.
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Journal Papers by Gibran Fuentes-Pineda
Papers by Gibran Fuentes-Pineda
Drafts by Gibran Fuentes-Pineda