Quadcopter see and avoid using a fuzzy controller

Unmanned Aerial Vehicles (UAVs) industry is a fast growing sector. Nowadays, the market offers numerous possibilities for off-the-shelf UAVs such as quadrotors or fixed-wings. Until UAVs demonstrate advance capabilities such as autonomous collision avoidance they will be segregated and restricted to flight in controlled environments. This work presents a visual fuzzy servoing system for obstacle avoidance using UAVs. To accomplish this task we used the visual information from the front camera. Images are processed off-board and the result send to the Fuzzy Logic controller which then send commands to modify the orientation of the aircraft. Results from flight test are presented with a commercial off-the-shelf platform.

Genetic fuzzy-based steering wheel controller using a mass-produced car

Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle to reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

Interactividad programada en el Game Engine de Blender

Con este proyecto se ha desarrollado una guía introductoria a uno de los aspectos más complejos y especializados de Blender, que es el control de su motor de videojuegos mediante programas escritos en Python. Está orientado a lectores que tienen un conocimiento amplio sobre el manejo de Blender, su interfaz y el funcionamiento de sus diferentes elementos, así como una mínima experiencia en cuanto a programación. Se ha organizado en una parte descriptiva, centrada en el lenguaje Python y en las bases de su uso para programar el motor de videojuegos (Game Engine) de Blender, y otra de práctica guiada, que constituye la mayoría del proyecto, donde se estudian de manera progresiva ejemplos concretos de uso del mismo. En la parte descriptiva se ha tratado tanto el funcionamiento más básico del lenguaje Python, especialmente las características que difieren de otros lenguajes de programación tradicionales, como su relación con Blender en particular, explicando las diferentes partes de la API de Blender para Python, y las posibles estrategias de uso. La parte práctica guiada, dado que esta interacción entre Blender y Python ofrece un rango de posibilidades muy amplio, se ha centrado en tres áreas concretas que han sido investigadas en profundidad: el control del objeto protagonista, de la cámara y la implementación de un mapa de orientación. Todas ellas se han centrado en torno a un ejemplo común, que consiste en un videojuego muy básico, y que, gracias a los ficheros de Blender que acompañan a esta memoria, sirve para apoyar las explicaciones y poder probar su efecto directamente. Por una parte, estos tres aspectos prácticos se han explicado exhaustivamente, y se han llevado hasta un nivel relativamente alto. Asimismo se han intentado minimizar las dependencias, tanto entre ellos como con la escena que se ha usado como ejemplo, de manera que sea sencillo usar los programas generados en otras aplicaciones. Por otra, la mayoría de los problemas que ha sido necesario resolver durante el desarrollo no son específicos de ninguna de las tres áreas, sino que son de carácter general, por lo que sus explicaciones podrán usarse al afrontar otras situaciones. ABSTRACT. This Thesis consists of an introductory guide to one of the most complex and specific parts of Blender, which is the control of its game engine by means of programs coded in Python. The dissertation is orientated towards readers who have a good knowledge of Blender, its interface and how its different systems work, as well as basic programming skills. The document is composed of two main sections, the first one containing a description of Python’s basics and its usage within Blender, and the second consisting of three practical examples of interaction between them, guided and explained step by step. On the first section, the fundamentals of Python have been covered in the first place, focusing on the characteristics that distinguish it from other programming languages. Then, Blender’s API for Python has also been introduced, explaining its different parts and the ways it can be used in. Since the interaction between Blender and Python offers a wide range of possibilities, the practical section has been centered on three particular areas. Each one of the following sections has been deeply covered: how to control the main character object, how to control the camera, and how to implement and control a mini-map. Furthermore, a demonstrative videogame has been generated for the reader to be able to directly test the effect of what is explained in each section. On the one hand, these three practical topics have been thoroughly explained, starting from the basis and gradually taking them to a relatively advanced level. The dependences among them, or between them and the demonstrative videogame, have been minimised so that the scripts or ideas can be easily used within other applications. On the other hand, most of the problems that have been addressed are not exclusively related to these areas, but will most likely appear in different situations, thus enlarging the field in which this Thesis can be used.

Game o la voluntad de romper el hielo

Creo que uno de los misterios más extraños que existen en nuestro país es el de las posibles causas por las que una especie de maleficio ha ido marcando el camino de la Microelectrónica. Pocos sectores de la tecnología han recibido un apoyo más constante y desde más entornos que ella y, al mismo tiempo, en pocos también se han obtenido menos frutos

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

A card Game Description Language

We present initial research regarding a system capable of generating novel card games. We furthermore propose a method for com- putationally analysing existing games of the same genre. Ultimately, we present a formalisation of card game rules, and a context-free grammar G cardgame capable of expressing the rules of a large variety of card games. Example derivations are given for the poker variant Texashold?em , Blackjack and UNO. Stochastic simulations are used both to verify the implementation of these well-known games, and to evaluate the results of new game rules derived from the grammar. In future work, this grammar will be used to evolve completely novel card games using a grammar- guided genetic program.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

The analysis of the basketball coach speech during the moments of game and pause in relation to the performance in competition

In the area of the professional competition, the coach is a fundamental part in the management of a team and more concretely in the game planning. During the competition, the management of the times of pause and times out as well as the conduct of the coach during the same ones is an aspect to analyze in the sports performance. It is for this that it becomes necessary to know some of the behaviors that turn out to be more frequent by the coach and that are more related to a positive performance of his players. For it there has been realized a study of 7 cases of expert coaches in those that his verbal behavior has observed during 4 games. It has focused on the content of the information only to verbal level, on his meaning. The information that have been obtained in the study shows a major quantity of information elaborated during the pauses of the games and a major tactical content with regard to the moments of game. On the other hand, a relation exists between a major number of questions and a minor number of psychological instructions when the score is adverse, whereas in case of victory, a direct relation does not exist with any category. The rest of categories of the speech do not meet influenced directly for the result, for what it is not possible to consider a direct and immediate relation between the coach verbal behavior during the pauses and the result of the game, except in punctual moments.

Ball possession effectiveness in men's and women's elite basketball according to situational variables in different game periods

The aim of the present study was to identify the importance of floorball tactical variables to predict ball possession effectiveness, when controlling quality of opposition and game periods. The sample was composed by 1500 ball possessions, corresponding to 14 games randomly selected from the International Championships played during 2008 and 2010 (World Championship, Four nations tournament and classificatory phases for World Championship) by teams from different competition levels (HIGH, INTERMEDIATE and LOW). The effects of the predictor variables on successful ball possessions according to the three game contexts (HIGH vs. HIGH; HIGH vs. LOW; LOW vs. LOW games) were analyzed using Binomial Logistic Regressions. The results showed no interaction with the game period. In HIGH vs. HIGH games, quality of opposition showed an association with ball possession effectiveness with ending zone, offensive system, possession duration, height of shooting and defensive pressures previous to the shot. In HIGH vs. LOW games the important factors were the starting zone, possession duration, defensive pressure previous to the last pass and to the shot, technique of shooting and the number players involved in each ball possession. Finally, in LOW vs. LOW games, the results emphasized the importance of starting and ending zones, the number of passes used and the technique of shooting. In conclusion, elite floorball performance is mainly affected by quality of opposition showing different game patterns in each context that should be considered by coaches when preparing practices and competitions.

Home automation controller for a water-flow window

Facing the EU energy efficiency and legal scenarios related to buildings (2010/31 EU directive), new sustainable advanced concepts for envelopes are required. These innovative designs must be able to offer an elevated level of energy efficiency based on a high performance architecture. According to this, smart glazings, and particularly active water-flow glazings, represent a promising alternative to other solar control glazings, since they can reduce the building energy demand avoiding well known drawbacks as high cost, glare problems and high response time that affect to other smart glazings. This kind of glazing, as any other active one, needs to be operated by a control system. In order to operate a water-flow based window, a new controller based on an inexpensive microcontroller board has been developed

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Self-Tuning PID controller for autonomous car tracking in urban traffic

In this paper an on line self-tuned PID controller is proposed for the control of a car whose goal is to follow another one, at distances and speeds typical in urban traffic. The bestknown tuning mechanism is perhaps the MIT rule, due to its ease of implementation. However, as it is well known, this method does not guarantee the stability of the system, providing good results only for constant or slowly varying reference signals and in the absence of noise, which are unrealistic conditions. When the reference input varies with an appreciable rate or in presence of noise, eventually it could result in system instability. In this paper an alternative method is proposed that significantly improves the robustness of the system for varying inputs or in the presence of noise, as demonstrated by simulation.

On-line learning of a fuzzy controller for a precise vehicle cruise control system

Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.

Geometric Study of the Weak Equilibrium in a Weighted Case for a Two-Dimensional Competition Game

In this work, an improvement of the results presented by [1] Abellanas et al. (Weak Equilibrium in a Spatial Model. International Journal of Game Theory, 40(3), 449-459) is discussed. Concretely, this paper investigates an abstract game of competition between two players that want to earn the maximum number of points from a finite set of points in the plane. It is assumed that the distribution of these points is not uniform, so an appropriate weight to each position is assigned. A definition of equilibrium which is weaker than the classical one is included in order to avoid the uniqueness of the equilibrium position typical of the Nash equilibrium in these kinds of games. The existence of this approximated equilibrium in the game is analyzed by means of computational geometry techniques.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.