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

Neural Learning of Stable Dynamical Systems based on Data-Driven Lyapunov Candidates

Neumann K, Lemme A, Steil JJ. Neural Learning of Stable Dynamical Systems based on Data-Driven Lyapunov Candidates. Presented at the Int. Conference Intelligent Robotics and Systems, Tokio

New representation of water activity based on a single solute specific constant to parameterize the hygroscopic growth of aerosols in atmospheric models

Water activity is a key factor in aerosol thermodynamics and hygroscopic growth. We introduce a new representation of water activity (<i>a</i><sub>w</sub>), which is empirically related to the solute molality (μ<sub>s</sub>) through a single solute specific constant, ν<sub><i>i</i></sub>. Our approach is widely applicable, considers the Kelvin effect and covers ideal solutions at high relative humidity (RH), including cloud condensation nuclei (CCN) activation. It also encompasses concentrated solutions with high ionic strength at low RH such as the relative humidity of deliquescence (RHD). The constant ν<sub><i>i</i></sub> can thus be used to parameterize the aerosol hygroscopic growth over a wide range of particle sizes, from nanometer nucleation mode to micrometer coarse mode particles. In contrast to other <i>a</i><sub>w</sub>-representations, our ν<sub><i>i</i></sub> factor corrects the solute molality both linearly and in exponent form <i>x · a<sup>x</sup></i>. We present four representations of our basic <i>a</i><sub>w</sub>-parameterization at different levels of complexity for different <i>a</i><sub>w</sub>-ranges, e.g. up to 0.95, 0.98 or 1. ν<sub><i>i</i></sub> is constant over the selected <i>a</i><sub>w</sub>-range, and in its most comprehensive form, the parameterization describes the entire <i>a</i><sub>w</sub> range (0–1). In this work we focus on single solute solutions. ν<sub><i>i</i></sub> can be pre-determined with a root-finding method from our water activity representation using an <i>a</i><sub>w</sub>−μ<sub>s</sub> data pair, e.g. at solute saturation using RHD and solubility measurements. Our <i>a</i><sub>w</sub> and supersaturation (Köhler-theory) results compare well with the thermodynamic reference model E-AIM for the key compounds NaCl and (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub> relevant for CCN modeling and calibration studies. Envisaged applications include regional and global atmospheric chemistry and climate modeling

OOP: Object-Oriented-Priority for Motion Saliency Maps

Belardinelli A, Schneider WX, Steil JJ. OOP: Object-Oriented-Priority for Motion Saliency Maps. In: Workshop on Brain Inspired Cognitive Systems. 2010: 370-381

Viabilidade de pupas de Thelosia camina schaus coletadas em plantios de erva-mate.

Resumo

Platform Portable Anthropomorphic Grasping with the Bielefeld 20-DOF Shadow and 9-DOF TUM Hand

Röthling F, Haschke R, Steil JJ, Ritter H. Platform Portable Anthropomorphic Grasping with the Bielefeld 20-DOF Shadow and 9-DOF TUM Hand. In: Proc. Int. Conf. on Intelligent Robots and Systems (IROS). IEEE; 2007: 2951-2956

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

Resumo

A fast stratospheric chemistry solver: the E4CHEM submodel for the atmospheric chemistry global circulation model EMAC

The atmospheric chemistry general circulation model ECHAM5/MESSy (EMAC) and the atmospheric chemistry box model CAABA are extended by a computationally very efficient submodel for atmospheric chemistry, E4CHEM. It focuses on stratospheric chemistry but also includes background tropospheric chemistry. It is based on the chemistry of MAECHAM4-CHEM and is intended to serve as a simple and fast alternative to the flexible but also computationally more demanding submodel MECCA. In a model setup with E4CHEM, EMAC is now also suitable for simulations of longer time scales. The reaction mechanism contains basic O3, CH4, CO, HOx, NOx, and ClOx gas phase chemistry. In addition, E4CHEM includes optional fast routines for heterogeneous reactions on sulphate aerosols and polar stratospheric clouds (substituting the existing submodels PSC and HETCHEM), and scavenging (substituting the existing submodel SCAV). We describe the implementation of E4CHEM into the MESSy structure of CAABA and EMAC. For some species the steady state in the box model differs by up to 100% when compared to results from CAABA/MECCA due to different reaction rates. After an update of the reaction rates in E4CHEM the mixing ratios in both boxmodel and 3-D model simulations are in satisfactory agreement with the results from a simulation where MECCA with a similar chemistry scheme was employed. Finally, a comparison against a simulation with a more complex and already evaluated chemical mechanism is presented in order to discuss shortcomings associated with the simplification of the chemical mechanism