Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure

Nitrogen compounds and ozone in the stratosphere: comparison of MIPAS satellite data with the Chemistry Climate Model ECHAM5/MESSy1

International audienceThe chemistry climate model ECHAM5/MESSy1 (E5/M1) in a setup extending from the surface to 80 km with a vertical resolution of about 600 m near the tropopause with nudged tropospheric meteorology allows a direct comparison with satellite data of chemical species at the same time and location. Here we present results out of a transient 10 years simulation for the period of the Antarctic vortex split in September 2002, where data of MIPAS on the ENVISAT-satellite are available. For the first time this satellite instrument opens the opportunity, to evaluate all stratospheric nitrogen containing species simultaneously with a good global coverage, including the source gas N2O which allows an estimate for NOx-production in the stratosphere. We show correlations between simulated and observed species in the altitude region between 10 and 50 hpa for different latitude belts, together with the Probability Density Functions (PDFs) of model results and observations. This is supplemented by global charts on pressure levels showing the satellite data and the simulated data sampled at the same time and location. We demonstrate that the model in most cases captures the partitioning in the nitrogen family, the diurnal cycles and the spatial distribution within experimental uncertainty. There appears to be, however, a problem to reproduce the observed nighttime partitioning between N2O5 and NO2 in the middle stratosphere

Caracterização populacional do nematoide Deladenus siricidicola, parasita da vespa-da-madeira Sirex noctilio.

Resumo

Simulation of polar stratospheric clouds in the chemistry-climate-model EMAC via the submodel PSC

The submodel PSC of the ECHAM5/MESSy Atmospheric Chemistry model (EMAC) has been developed to simulate the main types of polar stratospheric clouds (PSC). The parameterisation of the supercooled ternary solutions (STS, type 1b PSC) in the submodel is based on Carslaw et al. (1995b), the thermodynamic approach to simulate ice particles (type 2 PSC) on Marti and Mauersberger (1993). For the formation of nitric acid trihydrate (NAT) particles (type 1a PSC) two different parameterisations exist. The first is based on an instantaneous thermodynamic approach from Hanson and Mauersberger (1988), the second is new implemented and considers the growth of the NAT particles with the aid of a surface growth factor based on Carslaw et al. (2002). It is possible to choose one of this NAT parameterisation in the submodel. This publication explains the background of the submodel PSC and the use of the submodel with the goal of simulating realistic PSC in EMAC

Attractor Metadynamics in Adapting Neural Networks

Slow adaption processes, like synaptic and intrinsic plasticity, abound in the brain and shape the landscape for the neural dynamics occurring on substantially faster timescales. At any given time the network is characterized by a set of internal parameters, which are adapting continuously, albeit slowly. This set of parameters defines the number and the location of the respective adiabatic attractors. The slow evolution of network parameters hence induces an evolving attractor landscape, a process which we term attractor metadynamics. We study the nature of the metadynamics of the attractor landscape for several continuous-time autonomous model networks. We find both first- and second-order changes in the location of adiabatic attractors and argue that the study of the continuously evolving attractor landscape constitutes a powerful tool for understanding the overall development of the neural dynamics

Interannual variation patterns of total ozone and lower stratospheric temperature in observations and model simulations

We report results from a multiple linear regression analysis of long-term total ozone observations (1979 to 2000, by TOMS/SBUV), of temperature reanalyses (1958 to 2000, NCEP), and of two chemistry-climate model simulations (1960 to 1999, by ECHAM4.L39(DLR)/CHEM (=E39/C), and MAECHAM4-CHEM). The model runs are transient experiments, where observed sea surface temperatures, increasing source gas concentrations (CO2, CFCs, CH4, N2O, NOx), 11-year solar cycle, volcanic aerosols and the quasi-biennial oscillation (QBO) are all accounted for. MAECHAM4-CHEM covers the atmosphere from the surface up to 0.01 hPa ( 80 km). For a proper representation of middle atmosphere (MA) dynamics, it includes a parametrization for momentum deposition by dissipating gravity wave spectra. E39/C, on the other hand, has its top layer centered at 10 hPa ( 30 km). It is targeted on processes near the tropopause, and has more levels in this region. Despite some problems, both models generally reproduce the observed amplitudes and much of the observed lowlatitude patterns of the various modes of interannual variability in total ozone and lower stratospheric temperature. In most aspects MAECHAM4-CHEM performs slightly better than E39/C. MAECHAM4-CHEM overestimates the longterm decline of total ozone, whereas E39/C underestimates the decline over Antarctica and at northern mid-latitudes. The true long-term decline in winter and spring above the Correspondence to: W. Steinbrecht ([email protected]) Arctic may be underestimated by a lack of TOMS/SBUV observations in winter, particularly in the cold 1990s. Main contributions to the observed interannual variations of total ozone and lower stratospheric temperature at 50 hPa come from a linear trend (up to −10 DU/decade at high northern latitudes, up to −40 DU/decade at high southern latitudes, and around −0.7 K/decade over much of the globe), from the intensity of the polar vortices (more than 40 DU, or 8 K peak to peak), the QBO (up to 20 DU, or 2 K peak to peak), and from tropospheric weather (up to 20 DU, or 2 K peak to peak). Smaller variations are related to the 11-year solar cycle (generally less than 15 DU, or 1 K), or to ENSO (up to 10 DU, or 1 K). These observed variations are replicated well in the simulations. Volcanic eruptions have resulted in sporadic changes (up to −30 DU, or +3 K). At low latitudes, patterns are zonally symmetric. At higher latitudes, however, strong, zonally non-symmetric signals are found close to the Aleutian Islands or south of Australia. Such asymmetric features appear in the model runs as well, but often at different longitudes than in the observations. The results point to a key role of the zonally asymmetric Aleutian (or Australian) stratospheric anti-cyclones for interannual variations at high-latitudes, and for coupling between polar vortex strength, QBO, 11-year solar cycle and ENSO