José Manuel Pérez-Lorenzo

Audio-visual perception system for a humanoid robotic head.

One of the main issues within the field of social robotics is to endow robots with the ability to direct attention to people with whom they are interacting. Different approaches follow bio-inspired mechanisms, merging audio and visual cues to localize a person using multiple sensors. However, most of these fusion mechanisms have been used in fixed systems, such as those used in video-conference rooms, and thus, they may incur difficulties when constrained to the sensors with which a robot can be equipped. Besides, within the scope of interactive autonomous robots, there is a lack in terms of evaluating the benefits of audio-visual attention mechanisms, compared to only audio or visual approaches, in real scenarios. Most of the tests conducted have been within controlled environments, at short distances and/or with off-line performance measurements. With the goal of demonstrating the benefit of fusing sensory information with a Bayes inference for interactive robotics, this paper presents a system for localizing a person by processing visual and audio data. Moreover, the performance of this system is evaluated and compared via considering the technical limitations of unimodal systems. The experiments show the promise of the proposed approach for the proactive detection and tracking of speakers in a human-robot interactive framework.

The influence of different sensory cues as selection feedback and co-location in presence and task performance

For some applications based on virtual reality technology, presence and task performance are important factors to validate the experience. Different approaches have been adopted to analyse the extent to which certain aspects of a computer-generated environment may enhance these factors, but mainly in 2D graphical user interfaces. This study explores the influence of different sensory modalities on performance and the sense of presence experienced within a 3D environment. In particular, we have evaluated visual, auditory and active haptic feedback for indicating selection of virtual objects. The effect of spatial alignment between proprioceptive and visual workspaces (co-location) has also been analysed. An experiment has been made to evaluate the influence of these factors in a controlled 3D environment based on a virtual version of the Simon game. The main conclusions obtained indicate that co-location must be considered in order to determine the sensory needs during interaction within a virtual environment. This study also provides further evidence that the haptic sensory modality influences presence to a higher extent, and that auditory cues can reduce selection times. Conclusions obtained provide initial guidelines that will help designers to set out better selection techniques for more complex environments, such as training simulators based on VR technology, by highlighting different optimal configurations of sensory feedback.

A wiki as a common framework for promoting autonomous learning among university students

The process of adapting methodologically to European Credit Transfer System suffers from a lack in practical evaluations within the engineering field. One of the main competencies within the studies of telematics engineering is the development of skills related to behaving as technical consultants. This competency has been traditionally developed via publishing additional material through learning management systems; however, the approach followed within this study has promoted its development through the creation of practical guides within a wiki. The evaluation of this activity with students of different courses is presented herein, providing certain guidelines about its use as a support system for autonomous learning.

Classifying a New Descriptor Based on Marr's Visual Theory

Descriptors are a powerful tool in digital image analysis. Performance of tasks such as image matching and object recognition is strongly dependent on the visual descriptors that are used. The dimension of the descriptor has a direct impact on the time the analysis take, and less dimensions are desirable for fast matching. In this paper we use a type of region called curvilinear region. This approach is based on Marrs visual theory. Marr supposed that every object can be divided in its constituent parts, being this parts cylinders. So, we suppose also that in every image there must be curvilinear regions that are easy to detect. We propose a very short descriptor to use with these curvilinear regions in order to classify these regions for higher visual tasks.

An Approach to Visual Scenes Matching with Curvilinear Regions

This paper presents a biologically-inspired artificial vision system. The goal of the proposed vision system is to correctly match regions among several images to obtain scenes matching. Based on works that consider that humans perceive visual objects divided in its cons-tituent parts, we assume that a particular type of regions, called curvilinear regions, can be easily detected in digital images. These features are more complex than the basic features that human vision uses in the very first steps in the visual process. We assume that the curvilinear regions can be compared in their complexity to those features analysed by the IT cortex for achieving objects recognition. The approach of our system is similar to other existing methods that also use intermediate complexity features for achieving visual matching. The novelty of our system is the curvilinear features that we use.

Binaural lateral localization of multiple sources in real environments using a kurtosis-driven split-EM algorithm

Abstract In this work a method for an unsupervised lateral localization of simultaneous sound sources is presented. Following a binaural approach, the kurtosis-driven split-EM algorithm (KDS-EM) implemented is able to estimate the direction of arrival of relevant sound sources without knowing a priori their number. Information about the localization is integrated within a period of observation time to serve as an auditory memory in the context of social robotics. Experiments have been conducted using two types of observation times, one shorter with the purpose of analyzing its performance in a reactive level, and other longer that allows the analysis of its contribution as an input of the building process of the sorroundings auditory models that servesto drive a more deliberative behavior. The system has been tested in real and reverberant environments, achieving a good performance based on an over-modeling process that is able to isolate the location of the relevant sources from adverse acoustic effects, such as reverberations.

LifeBots I: Building the Software Infrastructure for Supporting Lifelong Technologies

The goal of the LifeBots project is the study and development of long-life mechanisms that facilitate and improve the integration of robotics platforms in smart homes to support elder and handicapped people. Specifically the system aims to design, build and validate an assistive ecosystem formed by a person living in a smart home with a social robot as her main interface to a gentler habitat. Achieving this goal requires the use and integration of different technologies and research areas, but also the development of the mechanisms in charge of providing an unified, pro-active response to the user’s needs. This paper describes some of the mechanisms implemented within the cognitive robotics architecture CORTEX that integrates deliberative and reactive agents through a common understanding and internalizing of the outer reality, which materializes in a shared representation derived from a formal graph grammar.

Curvilinear image regions detection: applications to mobile robotics

This paper proposes a novel approach for visual features detection, which is based on the presence of objects whose shape can be modelled using cylinders or generalized cylinders. These specific structures are commonly found on indoor and outdoor scenarios, and their image representations, the so-called curvilinear regions, automatically deform with changing viewpoint as to keep on covering identical physical parts of a scene. The method is based on Marrs visual theory that proposes that visual objects can be decomposed in generalized cylinders. Also, part of the method can be compared to the behavior of AOS neurons, placed in the caudal intraparietal sulcus, that respond when an elongated object is visualized. Our detector reliably finds the same curvilinear regions under different viewing conditions. Evaluation results are given to demonstrate the performance of the approach and its ability to be applied for visual features detection in a mobile robot navigation framework.

A Dual Graph Pyramid Approach to Grid-Based and Topological Maps Integration for Mobile Robotics

A pyramid is a hierarchy of successively reduced graphs which represents the contents of a base graph at multiple levels of abstraction. The efficiency of the pyramid to represent the information is strongly influenced by the graph selected to encode the information within each pyramid level (data structure) and the scheme used to build one graph from the graph below (decimation process). In this paper, the dual graph data structure and the maximal independent edge set (MIES) decimation process are applied in the context of robot navigation. The aim is to integrate the grid-based and the topological paradigms for map building. In this proposal, dual graphs allow to correctly represent the embedding of the topological map into the metric one.