URBANO: A Tour-Guide Robot Learning to Make Better Speeches

—Thanks to the numerous attempts that are being made to develop autonomous robots, increasingly intelligent and cognitive skills are allowed. This paper proposes an automatic presentation generator for a robot guide, which is considered one more cognitive skill. The presentations are made up of groups of paragraphs. The selection of the best paragraphs is based on a semantic understanding of the characteristics of the paragraphs, on the restrictions defined for the presentation and by the quality criteria appropriate for a public presentation. This work is part of the ROBONAUTA project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality of the presentations. To achieve this goal, the system has to perform the optimized decision making, in different phases. The modeling of the quality index of the presentation is made using fuzzy logic and it represents the beliefs of the robot about what is good, bad, or indifferent about a presentation. This fuzzy system is used to select the most appropriate group of paragraphs for a presentation. The beliefs of the robot continue to evolving in order to coincide with the opinions of the public. It uses a genetic algorithm for the evolution of the rules. With this tool, the tour guide-robot shows the presentation, which satisfies the objectives and restrictions, and automatically it identifies the best paragraphs in order to find the most suitable set of contents for every public profil

Learning to Be a Good Tour-Guide Robot

Thanks to the numerous attempts that are being made to develop autonomous robots, increasingly intelligent and cognitive skills are allowed. This paper proposes an automatic presentation generator for a robot guide, which is considered one more cognitive skill. The presentations are made up of groups of paragraphs. The selection of the best paragraphs is based on a semantic understanding of the characteristics of the paragraphs, on the restrictions defined for the presentation and by the quality criteria appropriate for a public presentation. This work is part of the ROBONAUTA project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality of the presentations. To achieve this goal, the system has to perform the optimized decision making, in different phases. The modeling of the quality index of the presentation is made using fuzzy logic and it represents the beliefs of the robot about what is good, bad, or indifferent about a presentation. This fuzzy system is used to select the most appropriate group of paragraphs for a presentation. The beliefs of the robot continue to evolving in order to coincide with the opinions of the public. It uses a genetic algorithm for the evolution of the rules. With this tool, the tour guide-robot shows the presentation, which satisfies the objectives and restrictions, and automatically it identifies the best paragraphs in order to find the most suitable set of contents for every public profile

Generador Automático de Presentaciones para Robot-Guía

En el ámbito de la robótica, los robots autónomos tienen una importancia cada vez mayor. Bekey los define como intelligent machines capable of performing tasks in the world by themselves, without explicit human control over their actions. l robot Urbano es una plataforma B21r de iRobot, equipada con un sistema de locomoción compuesto por cuatro ruedas, un láser tipo SICK LMS200 montado horizontalmente en la parte superior de la plataforma para la navegación y SLAM, y una cara y brazos robóticos que utiliza para expresar emociones como alegría, tristeza, sorpresa o enfado

Automatic Presentations Generation Based on Patterns for Tour-Guide Robots

This paper proposes an automatic presentation generation for a tour-guide robot making use of natural language processing and patterns. To reach a suitable approximation in a believable presentation some parameters are identified and described in this paper. Automatic Presentations Generation is based on XML-patterns. The generation process selects information items and obtains the prone of the tree with fuzzy rules

Improving web learning through model optimization using bootstrap for a tour-guide robot

We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology applied to pattern model classifier optimization and verification for Supervised Learning for Tour-Guide Robot knowledge repository management. It is virtually impossible to test thoroughly Web Page Classifiers and many other Internet Applications with pure empirical data, due to the need for human intervention to generate training sets and test sets. We propose using the computer-based Bootstrap paradigm to design a test environment where they are checked with better reliability

Engineering Education through eLearning technology in Spain

eLearning kind of education is stirring up all the disciplines in the academic circles, especially since it provides an access to educational areas that are uneasy and traditionally in-person, such as Engineering. Even though it had an outbreak in some of the most prestigious American universities, eLearning has being a reality in Spain for some years now, changing educational and teaching habits. To ensure a proper education is not an easy task with it comes to engineering fields, therefore this article shows an update on the works developed on this issue and the technologies they used. In this report it is given a perspective of the intimate relationship between the eLearning method of learning and the studies of Engineering in Spain, through the TIC development and the current educational legislation. In this regard, teaching examples are given on several subjects of different engineering studies, emphasizing the good results obtained in the abovementioned experiences. Below here is a evaluation on the results obtained in the analyzed studies

Decision-Making Mechanism to Organize the Agenda of a Guide-Robot

One of the major challenges in evolutionary robotics is constituted by the need of the robot being able to make decisions on its own, in accordance with the multiple tasks programmed, optimizing its timings and power. In this paper, we present a new automatic decision making mechanism for a robot guide that allows the robot to make the best choice in order to reach its aims, performing its tasks in an optimal way. The election of which is the best alternative is based on a series of criteria and restrictions of the tasks to perform. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality in the decision making. The modeling of the quality index of the best choice to perform is made using fuzzy logic and it represents the beliefs of the robot, which continue to evolve in order to match the "external reality”. This fuzzy system is used to select the most appropriate set of tasks to perform during the day. With this tool, the tour guide-robot prepares its agenda daily, which satisfies the objectives and restrictions, and it identifies the best task to perform at each moment. This work is part of the ARABOT project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide

Engineering education through elearning technology in spain

eLearning kind of education is stirring up all the disciplines in the academic circles, especially since it provides an access to educational areas that are uneasy and traditionally in-person, such as Engineering. Even though it had an outbreak in some of the most prestigious American universities, eLearning has being a reality in Spain for some years now, changing educational and teaching habits. To ensure a proper education is not an easy task with it comes to engineering fields, therefore this article shows an update on the works developed on this issue and the technologies they used. In this report it is given a perspective of the intimate relationship between the eLearning method of learning and the studies of Engineering in Spain, through the TIC development and the current educational legislation. In this regard, teaching examples are given on several subjects of different engineering studies, emphasizing the good results obtained in the abovementioned experiences. Below here is a evaluation on the results obtained in the analyzed studies

Real-Time Visual Recognition of Ramp Hand Signals for UAS Ground Operations

We describe the design and validation of a vision-based system that allows the dynamic identification of ramp signals performed by airport ground staff. This ramp signals’ recognizer increases the autonomy of unmanned vehicles and prevents errors caused by visual misinterpretations or lack of attention from the pilot of manned vehicles. This system is based on supervised machine learning techniques, developed with our own training dataset and two models. The first model is based on a pre-trained Convolutional Pose Machine followed by a classifier, for which we have evaluated two possibilities: A Random Forest and a Multi-Layer Perceptron based classifier. The second model is based on a single Convolutional Neural Network that classifies the gestures directly imported from real images. When experimentally tested, the first model proved to be more accurate and scalable than the second one. Its strength relies on a better capacity to extract information from the images and transform the domain of pixels into spatial vectors, which increases the robustness of the classification layer. The second model instead is more adequate for gestures’ identification in low visibility environments, such as during night operations, conditions in which the first model appeared to be more limited, segmenting the shape of the operator. Our results support the use of supervised learning and computer vision techniques for the correct identification and classification of ramp hand signals performed by airport marshallers.Peer reviewe