http://hdl.handle.net/10045/21355 Wed, 22 May 2013 11:55:46 GMT 2013-05-22T11:55:46Z http://rua.ua.es:80/dspace/retrieve/88558/cover_issue_21_en_US.jpg http://hdl.handle.net/10045/21355 http://hdl.handle.net/10045/21361 Título: Learning in real robots from environment interaction Autor/es: Quintía Vidal, Pablo; Iglesias Rodríguez, Roberto; Rodríguez González, Miguel Ángel; Vázquez Regueiro, Carlos; Valdés Villarrubia, Fernando Resumen: This article describes a proposal to achieve fast robot learning from its interaction with the environment. Our proposal will be suitable for continuous learning procedures as it tries to limit the instability that appears every time the robot encounters a new situation it had not seen before. On the other hand, the user will not have to establish a degree of exploration (usual in reinforcement learning) and that would prevent continual learning procedures. Our proposal will use an ensemble of learners able to combine dynamic programming and reinforcement learning to predict when a robot will make a mistake. This information will be used to dynamically evolve a set of control policies that determine the robot actions. Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/10045/21361 2012-01-01T00:00:00Z http://hdl.handle.net/10045/21360 Título: Multi-agent system for fast deployment of a guide robot in unknown environments Autor/es: Canedo Rodríguez, Adrián; Álvarez Santos, Víctor; Vázquez Regueiro, Carlos; Pardo López, Xose Manuel; Iglesias Rodríguez, Roberto Resumen: Nowadays, deploying service robots and adapting their services to a new environment is a task which might require several days. This is an important problem of robotics in general, but specially when the goal is to bring robots to our everyday life. In this paper we present a multi-agent intelligent space, which consists on intelligent cameras and autonomous guide robots. The deployment of the system does not require expertise and can be done in a short period of time. The cameras detect situations requiring the robots’ guiding services, inform the robots accordingly, and support the robots navigation towards the goal areas, without the need of a map of the environment. An example of these situations requiring the robot guide service could be a group of persons entering a museum. In this sense, we also present an adaptive person follower behaviour intended to be the basis of a route learning process, necessary to offer the guide service. Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/10045/21360 2012-01-01T00:00:00Z http://hdl.handle.net/10045/21359 Título: Local robot navigation based on an active visual short-term memory Autor/es: Vega Pérez, Julio; Cañas Plaza, José María; Perdices García, Eduardo Resumen: Vision devices are today one of the most often used sensory elements in autonomous robots. Some of their hindrances are the difficulty in extracting useful information from the captured images and the small visual field of regular cameras. Visual attention systems and active vision may help to overcome them. This work proposes a dynamic visual memory to store the information gathered from a continuously moving camera onboard the robot and an attention system to choose where to look at with such mobile camera. The visual memory is a collection of relevant task-oriented objects and 3D segments, and its scope is wider than instantaneous field of view of the camera. The attention system takes into account the need to reobserve objects in the visual memory, explore new areas and test hypothesis about object existence in the robot surroundings. The system has been programmed and validated in a real Pioneer robot that uses the information in the visual memory for navigation tasks. Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/10045/21359 2012-01-01T00:00:00Z http://hdl.handle.net/10045/21358 Título: Obstacle avoidance in underwater glider path planning Autor/es: Isern González, Josep; Hernández Sosa, Daniel; Fernández Perdomo, Enrique; Cabrera Gámez, Jorge; Domínguez Brito, Antonio Carlos; Prieto Marañón, Víctor Resumen: Underwater gliders have revealed as a valuable scientific platform, with a growing number of successful environmental sampling applications. They are specially suited for long range missions due to their unmatched autonomy level, although their low surge speed make them strongly affected by ocean currents. Path planning constitute a real concern for this type of vehicle, as it may reduce the time taken to reach a given waypoint or save power. In such a dynamic environment it is not easy to find an optimal solution or any such requires large computational resources. In this paper, we present a path planning scheme with low computational cost for this kind of underwater vehicle that allows static or dynamic obstacle avoidance, frequently demanded in coastal environments, with land areas, strong currents, shipping routes, etc. The method combines an initialization phase, inspired by a variant of the A* search process and ND algorithm, with an optimization process that embraces the physical vehicle motion pattern. Consequently, our method simulates a glider affected by the ocean currents, while it looks for the path that optimized a given objective. The method is easy to configure and adapt to various optimization problems, including missions in different operational scenarios. This planner shows promising results in realistic simulations, including ocean currents that vary considerably in time, and provides a superior performance over other approaches that are compared in this paper. Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/10045/21358 2012-01-01T00:00:00Z