Body and leg coordination for omni-directional walking in rough terrain

International Conference on Climbing and Walking Robots (CLAWAR), 2000, Madrid (España)In this paper, we address the problem of moving a legged robot in an unknown environment according to externally provided driving commands assuming an arbitrary initial position of legs. This general problem is decomposed in three subproblems: first, decide when to lift a given leg, second, choose where to move lifted legs, and third, coordinate body and leg movements to make the robot advance in the desired direction. To solve this third problem, we extend the posture control mechanism introduced in (1) so that body movements are limited to the desired trajectory. The resulting controller performs smooth transitions between different trajectories and can cope with irregular terrain where valid footholds are scarce.This work was supported by the project 'Navegación basada en visión de robots autónomos en entornos no estructurados.' (070-724).Peer Reviewe

Reinforcement Learning for Agents with Many Sensors and Actuators Acting in Categorizable Environments

In this paper, we confront the problem of applying reinforcement learning to agents that perceive the environment through many sensors and that can perform parallel actions using many actuators as is the case in complex autonomous robots. We argue that reinforcement learning can only be successfully applied to this case if strong assumptions are made on the characteristics of the environment in which the learning is performed, so that the relevant sensor readings and motor commands can be readily identified. The introduction of such assumptions leads to strongly-biased learning systems that can eventually lose the generality of traditional reinforcement-learning algorithms. In this line, we observe that, in realistic situations, the reward received by the robot depends only on a reduced subset of all the executed actions and that only a reduced subset of the sensor inputs (possibly different in each situation and for each action) are relevant to predict the reward. We formalize this property in the so called 'categorizability assumption' and we present an algorithm that takes advantage of the categorizability of the environment, allowing a decrease in the learning time with respect to existing reinforcement-learning algorithms. Results of the application of the algorithm to a couple of simulated realistic-robotic problems (landmark-based navigation and the six-legged robot gait generation) are reported to validate our approach and to compare it to existing flat and generalization-based reinforcement-learning approaches

La persecución de un imposible: dictadura y aperturismo. El diario Ya durante el régimen de Franco

Ya se convirtió en un importante apoyo al régimen de Franco a partir de 1952. Pero antes debió soportar un director impuesto, quedando fuertemente controlado por el gobierno: su empresa editora resultaba sospechosa porque había aceptado la Segunda República (1931-1936). Entre 1953 y 1959 vivió una época de expansión y también de radicales divisiones internas, entre los partidarios del régimen de Franco y los contrarios a él. Ya siguió las orientaciones de Ángel Herrera Oria: la apertura hacia otras fuerzas (los “restos católicos” de la Institución Libre de Enseñanza) para ampliar la base del régimen de Franco y sostenerlo. Finalmente, los sectores que no apoyaban estos planes fueron expulsados de la empresa. A partir de 1966 hubo cierta libertad de prensa. El objetivo de Ya fue entonces la apertura política desde las instituciones franquistas. Demandó un aumento del pluralismo ideológico y de la representatividad de las instituciones. Las ideas de Ya resultaban contradictorias: era imposible crear un sistema político democrático sin herir de muerte a la dictadura. Tras la muerte de Franco la transición empleó elementos válidos que el sistema anterior ofrecía. Esto fue lo que propuso entre 1973 y 1975 el grupo Tácito, originado en la redacción de Ya

Effects of complementary grazing by goats on sward composition and on sheep performance managed during lactation in perennial ryegrass and white clover pastures

The liveweight (LW) response of Gallega and Lacha ewes with their single suckling lambs when grazing with a mob of goats on perennial ryegrass (Lolium perenne L.)/white clover (Trifolium repens L.) pastures and its consequence on sward composition were analysed. From early March (turnout) to mid-June (lamb weaning), swards were grazed either simultaneously mixed in a 1:1 goat to sheep ratio or separately in a goat-first and sheep-last sequential grazing at 6 or 8 cm sward heights or in a 4-paddock rotation where goats grazed swards from 9 to 7 cm followed by sheep from 7 to 4 cm. Changes in botanical composition and in sheep liveweight performance were more significantly affected by the management and species grazing than by the sward height treatment. Swards where goats were last in had higher herbage masses, higher live clover and lower dead and stem proportions than swards where sheep and goats were mixed or sheep were last in. As a consequence of a sward clover enhancement over all treatments, ewe and lamb performances were benefited especially in the Lacha genotype, with the rotational and sequential managements having, respectively, an output of 298 and 252 kg LW/ha greater than the mixed management. These results suggest that goats could be used as a pasture management tool when integrated with sheep under these different grazing systems to enhance ovine performance during lactation