Observação e análise da utilização da mini-linguagem Karel the robot num modelo de ensino para aprendizagem de programação no 10º ano do Curso Tecnológico de Informática

O grande objectivo deste estudo foi contribuir para a melhoria do ensino da programação de computadores para aluno principiantes, através de um processo de observação da relação pedagógica estabelecida em sala de aula.

Predicting intention to work with social robots

The growing number of robotic solutions geared to interact socially with humans, social robots, urge the study of the factors that will facilitate or hinder future human robot collaboration. Hence the research question: what are the factors that predict intention to work with a social robot in the near future. To answer this question the following socio-cognitive models were studied, the theory of reasoned action, the theory of planned behavior and the model of goal directed behavior. These models purport that all the other variables will only have an indirect effect on behavior. That is, through the variables of the model. Based on the research on robotics and social perception/ cognition, social robot appearance, belief in human nature uniqueness, perceived warmth, perceived competence, anthropomorphism, negative attitude towards robots with human traits and negative attitudes towards interactions with robots were studied for their effects on attitude towards working with a social robot, perceived behavioral control, positive anticipated emotions and negative anticipated emotions. Study 1 identified the social representation of robot. Studies 2 to 5 investigated the psychometric properties of the Portuguese version of the negative attitude towards robots scale. Study 6 investigated the psychometric properties of the belief in human nature uniqueness scale. Study 7 tested the theory of reasoned action and the theory of planned behavior. Study 8 tested the model of goal directed behavior. Studies 7 and 8 also tested the role of the external variables. Study 9 tested and compared the predictive power of the three socio-cognitive models. Finally conclusion are drawn from the research results, and future research suggestions are offered.

Biologically Inspired Vision for Indoor Robot Navigation

Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.