Uma contribuição ao estudo de sinais de EEG para avaliar estados emocionais e mentais de crianças com autismo na interação com robô móvel

O Transtorno do Espectro do Autismo (TEA) caracteriza-se por uma série de distúrbios cognitivos e neurocomportamentais e sua prevalência mundial é estimada em 1 criança com TEA a cada 160 crianças com típico desenvolvimento (TD). Indivíduos com TEA apresentam dificuldade em interpretar as emoções alheias e em expressar sentimentos. As emoções podem ser associadas à manifestação de sinais fisiológicos, e, dentre eles, os sinais cerebrais têm sido muito abordados. A detecção dos sinais cerebrais de crianças com TEA pode ser benéfica para o esclarecimento de suas emoções e expressões. Atualmente, muitas pesquisas integram a robótica ao tratamento pedagógico do TEA, através da interação com crianças com esse transtorno, estimulando habilidades sociais, como a imitação e a comunicação. A avaliação dos estados mentais de crianças com TEA durante a sua interação com um robô móvel é promissora e assume um aspecto inovador. Assim, os objetivos deste trabalho foram captar sinais cerebrais de crianças com TEA e de crianças com TD, como grupo controle, para o estudo de seus estados emocionais e para avaliar seus estados mentais durante a interação com um robô móvel, e avaliar também a interação dessas crianças com o robô, através de escalas quantitativas. A técnica de registro dos sinais cerebrais escolhida foi a eletroencefalografia (EEG), a qual utiliza eletrodos colocados de forma não invasiva e não dolorosa sobre o couro cabeludo da criança. Os métodos para avaliar a eficiência do uso da robótica nessa interação foram baseados em duas escalas internacionais quantitativas: Escala de Alcance de Metas (do inglês Goal Attainment Scaling - GAS) e Escala de Usabilidade de Sistemas (do inglês System Usability Scale - SUS). Os resultados obtidos mostraram que, pela técnica de EEG, foi possível classificar os estados emocionais de crianças com TD e com TEA e analisar a atividade cerebral durante o início da interação com o robô, através dos ritmos alfa e beta. Com as avaliações GAS e SUS, verificou-se que o robô móvel pode ser considerado uma potencial ferramenta terapêutica para crianças com TEA.

Navegação de um robô autónomo semi-industrial usando diferentes técnicas sensoriais

Mestrado em Engenharia Electrotécnica e de Computadores

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

Planeamento de rota em ambiente desconhecido

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Auxiliary mechanisms for telerobotics

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Enhanced PCA-based localization using depth maps with missing data

In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

Perspectives and approaches for the internet of things

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

WMR navigation using local potential field corridors and narrow local occupancy grid perception

Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

An overview of the advantages and constraints of coded pattern projection techniques for autonomous navigation

The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

Kaukokäyttöliittymä liikkuvalle robotille

Lappeenrannan teknillinen yliopiston Tietotekniikan osaston Tietojenkäsittelytieteen laitoksen tutkimuskäytössä olevaan liikkuvaan robottiin toteutettiin tässä työssä graafinen kaukokäyttöliittymä. Työlle on motivaationa laajennettavuus, jota olemassaoleva suljetun lähdekoodin käyttöliittymä ei pysty tarjoamaan. Työssä olennaisin on olio-ohjelmointitekniikalla toteutettu robotin datamallin, ja sen graafisen esityksen arkkitehtuurillinen erottaminen. Lisäksi tarkastellaan lyhyesti liikkuvien robottien kaukokäyttöliittymien teoriaa, ja WLAN-tekniikan soveltuvuutta robotin ja käyttöliittymän välisen yhteyden toteuttamiseen.

AVR-pohjainen mobiilirobotti

Kandidaatintyön aineena oli rakentaa autonomisesti pyörillä liikkuva, esteitä väistelevä mobiilirobotti käyttäen Arduino-kehitysympäristöä prototyypin valmistamiseen. Rakensin robotin alusta alkaen itse eli työhön sisältyi robotin mekaniikan kokoaminen, elektroniikan suunnittelu ja rakentaminen sekä toimintaälyn ohjelmointi mikroprosessorille eteenpäin kulkemiseen ja esteiden väistämiseen. Arduinon ytimenä on Atmelin AVR-sarjaan kuuluva ATMega328-mikroprosessori. Robotin ympäristön havainnointi tapahtuu käyttämällä ultraäänisensoria. Robotti oli mielenkiintoinen projekti toteuttaa ja toimi kokonaisuutena katsottuna odotetulla tavalla.

A Colony Architecture for an Artificial Creature

This report describes a working autonomous mobile robot whose only goal is to collect and return empty soda cans. It operates in an unmodified office environment occupied by moving people. The robot is controlled by a collection of over 40 independent "behaviors'' distributed over a loosely coupled network of 24 processors. Together this ensemble helps the robot locate cans with its laser rangefinder, collect them with its on-board manipulator, and bring them home using a compass and an array of proximity sensors. We discuss the advantages of using such a multi-agent control system and show how to decompose the required tasks into component activities. We also examine the benefits and limitations of spatially local, stateless, and independent computation by the agents.

MARVEL: A System for Recognizing World Locations with Stereo Vision

To use a world model, a mobile robot must be able to determine its own position in the world. To support truly autonomous navigation, I present MARVEL, a system that builds and maintains its own models of world locations and uses these models to recognize its world position from stereo vision input. MARVEL is designed to be robust with respect to input errors and to respond to a gradually changing world by updating its world location models. I present results from real-world tests of the system that demonstrate its reliability. MARVEL fits into a world modeling system under development.