Spline in JavaVis

A Spline for camera movement in JavaVis.

El Plan Bonet, 1961-64. La condición del paisaje en la ordenación del desarrollo turístico de La Manga del Mar Menor

En el contexto rural de Murcia, la recepción de la modernidad fue un fenómeno episódico y tardío. Hacia 1960 se produjo, sin embargo, un breve e ilusionante periodo cuando algunos maestros de la arquitectura española llegaron para trabajar en el desarrollo turístico de un litoral virgen y lleno de oportunidades. Entre ellos, Antoni Bonet recibió el encargo de urbanizar La Manga, una estrecha franja de tierra de 24km que separa el Mediterráneo del Mar Menor. El Plan retomaba los planteamientos urbanos de Le Corbusier para reelaborar algunas ideas preparatorias: autonomía y jerarquía de los núcleos habitados, eje vertebrador, centro cívico al borde del mar, tratamiento del frente marítimo con islas artificiales. Minimizando su impacto en el ecosistema dunar con una carretera elevada puntualmente para favorecer el aporte de arena, el Plan concentraba la edificación alrededor de torres de 16 plantas, generando unidades compactas de viviendas y equipamientos repetidas cada 2km. Inspirándose en la lectura del territorio de Le Corbusier en Buenos Aires (1929), Bonet respondía a la horizontalidad del plano del mar por contraste topológico, subrayando la presencia vertical de las torres como hitos paisajísticos que, desde la orilla opuesta, marcaban la posición de cada núcleo.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.