Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence

Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering system, which is capable of detecting and displaying surface roughness. As the robot fingertip moves across a surface of interest, two microphones capture sound coupled directly through the fingertip and through the air, respectively. A learning-based detector system analyzes the data in real time and gives roughness estimates with both high temporal resolution and low latency. Finally, an audio-based vibrational actuator displays the result to the human operator. We demonstrate the effectiveness of our system through lab experiments and our winning entry in the ANA Avatar XPRIZE competition finals, where briefly trained judges solved a roughness-based selection task even without additional vision feedback. We publish our dataset used for training and evaluation together with our trained models to enable reproducibility of results.Comment: IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Hawaii, USA, October 202

Robust Immersive Telepresence and Mobile Telemanipulation: NimbRo wins ANA Avatar XPRIZE Finals

Robotic avatar systems promise to bridge distances and reduce the need for travel. We present the updated NimbRo avatar system, winner of the $5M grand prize at the international ANA Avatar XPRIZE competition, which required participants to build intuitive and immersive robotic telepresence systems that could be operated by briefly trained operators. We describe key improvements for the finals, compared to the system used in the semifinals: To operate without a power- and communications tether, we integrated a battery and a robust redundant wireless communication system. Video and audio data are compressed using low-latency HEVC and Opus codecs. We propose a new locomotion control device with tunable resistance force. To increase flexibility, the robot's upper-body height can be adjusted by the operator. We describe essential monitoring and robustness tools which enabled the success at the competition. Finally, we analyze our performance at the competition finals and discuss lessons learned.Comment: M. Schwarz and C. Lenz contributed equall

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

Spatio-temporal modelling of residential exposure to particulate matter and gaseous pollutants for the Heinz Nixdorf Recall Cohort

For the simultaneous analysis of short-and long-term effects of air pollution in the Heinz Nixdorf Recall Cohort a sophisticated exposure modelling was performed. The dispersion and chemistry transport model EURAD (European Air Pollution Dispersion) was used for the estimation of hourly concentrations of a number of pollutants for a horizontal grid with a cell size of 1 km(2) covering the whole study area (three large adjacent cities in a highly urbanized region in Western Germany) for the years 2000-2003 and 2006-2008. For each 1 km(2) cell we estimated the mean concentration by calculating daily means from the hourly concentrations modelled by the EURAD process. The modelled concentrations showed an overall tendency to decrease from 2001 to 2008 whereas the trend in the single grid cells and study period was inhomogeneous. Participant-related exposure slightly increased from 2001 to 2003 followed by a decrease from 2006 to 2008. The exposure modelling enables a very flexible exposure assessment compared to conventional modelling approaches which either use central monitoring or temporally static spatial contrasts. The modelling allows the calculation of an average exposure concentration for any place and time within the study region and study period with a high spatial and temporal resolution. This is important for the assessment of short-, medium and long-term effects of air pollution on human health in epidemiological studies. (C) 2014 Elsevier Ltd. All rights reserved

Comparison of four years of air pollution data with a mesoscale model

Air quality within the European Union (EU) is controlled by the Member States' monitoring networks. In this study, measured data is compared with the EURAD (EURopean Air pollution Dispersion) model system diagnostic output Simulations for the German state North Rhine-Westphalia (NRW) with a horizontal grid resolution of 5 km x 5 km are analyzed. The comparison is performed for NO2, O-3, and PM10, for the 4-year time period from 2002 through 2005. Although the spatial representativity of data of the two systems differs, the analyzed temporal variability of the averages shows good agreement of modeled and observed concentrations for all three parameters. This confirms the applicability of the EURAD model to mesoscale air quality assessment. Discrepancies between the model and observed data occurred at low concentrations close to the detection limits of the analyzers, for high O-3 concentrations in summer, and for PM10 before 2004, when earlier versions of the MM5 meteorological module and of the emission inventory were used. Possible causes of O-3 overprediction and NO2 underprediction preferably showing up in summer are considered. It is found that modeled O-x = O-3 + NO2 leads to better representation of the observations than the individual species themselves. The model performance can probably be increased by further development of the emission inventories and more accurate land use data. These input data seem to be the main reason for deviations between observations and model results. (C) 2012 Elsevier B.V. All rights reserved

Regional and local effects of electric vehicles on air quality and noise

Road traffic is one of the main causes of poor air quality in European cities. The air pollution burden due to road traffic in a street canyon consists of shares from local traffic and contributions of vehicles driving elsewhere in the city as well as elsewhere on a larger scale. Are electric vehicles a solution for air quality problems in cities? Do they reduce noise levels in street canyons significantly? The aim of this sensitivity study is to investigate the regional and local effects of electric vehicles on noise and air quality taking possible effects of additional electricity production into account. Focus of the present study lies for air quality on the regional scale in North Rhine-Westphalia and the overall effect in some selected street canyons, to be more precise the annual average PM10 and NO2 concentrations. A sensitivity study using the chemistry transport model EURAD and a screening model for street canyons was carried out. The influence on noise levels was analysed based on measurements of vehicles at different speeds. It turns out that road traffic has a significant impact on the regional air pollution levels. Furthermore it is shown that the reduction potential is bigger for NO2 than for PM10. With regard to EC limit value compliance a major share of electric vehicles could be a solution for the NO2 problems in moderately polluted street canyons. One of our findings is that if the additional electricity need causes additional emissions these counteract the possible reduction, especially for PM10. The noise reduction potential of electric vehicles is only significant for vehicles moving at low speeds

Urban Particulate Matter Air Pollution Is Associated With Subclinical Atherosclerosis Results From the HNR (Heinz Nixdorf Recall) Study

Objectives The aim of this study was to investigate the association of long-term residential exposure to fine particles with carotid intima-media thickness (CIMT). Background Experimental and epidemiological evidence suggest that long-term exposure to air pollution might have a causal role in atherogenesis, but epidemiological findings are still inconsistent. We investigate whether urban particulate matter (PM) air pollution is associated with CIMT, a marker of subclinical atherosclerosis. Methods We used baseline data (2000 to 2003) from the HNR (Heinz Nixdorf Recall) study, a population-based cohort of 4,814 participants, 45 to 75 years of age. We assessed residential long-term exposure to PM with a chemistry transport model and measured distance to high traffic. Multiple linear regression was used to estimate associations of air pollutants and traffic with CIMT, adjusting for each other, city of residence, age, sex, diabetes, and lifestyle variables. Results Median CIMT of the 3,380 analyzed participants was 0.66 mm (interquartile range 0.16 mm). An interdecile range increase in PM2.5 (4.2 mu g/m(3)), PM10 (6.7 mu g/m(3)), and distance to high traffic (1,939 m) was associated with a 4.3% (95% confidence interval [CI]: 1.9% to 6.7%), 1.7% (95% CI: -0.7% to 4.1%), and 1.2% (95% CI: -0.2% to 2.6%) increase in CIMT, respectively. Conclusions Our study shows a clear association of long-term exposure to PM2.5 with atherosclerosis. This finding strengthens the hypothesized role of PM2.5 as a risk factor for atherogenesis. (J Am Coll Cardiol 2010;56:1803-8) (C) 2010 by the American College of Cardiology Foundatio