Pose-estimation

Ye, M., Wang, X., Yang, R., Ren, L. Pollefeys, M. (2011). Accurate 3d pose estimation from a single depth image. IEEE International Conference on Computer Vision (ICCV), 731-738. 

Kruger, V., Bruns, S. and Sommer, G. (2000) Efficient head pose estimation with Gabor wavelet networks. In Proceedings of the IF British Machine Vision Conference, University of Bristol. UK, pp. 72-81. 

Dudek, and Milios (2000), Rekleitis, Dudek, and Milios (2002), and Rekleitis, Dudek, and Milios (2003). A team of two robots is considered during exploration. Each platform is equipped with a robot tracker sensor to retrieve relative positions between robots. A particle filter is exploited to update pose estimates and the attached uncertainty. 

This chapter deals with the design of a completely decentralized and distributed multi-robot localization algorithm. The localization procedure is based on nonlinear filtering. Specifically, it is an interlaced version of the EKF, able to produce accurate pose estimation for each robot of the team, thereby considerably reducing the computational load. 

Kalman Filter is a data fusion methodology used to combine position sensor data to obtain the best next possible pose estimation and correct real-localization ofthe robot. The next section will show how we used the Kalman Filter in our work. 

Figure 9 shows the results of the Kalman-Filter-based method for the pose estimate applied in the robot s trajectory which has triangulation measurements marked by yellow crosses. In this experimental result, we allocated four beacons. 

Figure 3 Pose estimation with structured light sensor.

PreGrasp Pose Estimation of Objects Using Local Sensors on Dexterous Hands... 

The pose estimation problem will be solved using a triangulation scheme to develop the equations and software based on a nonlinear least-squares algorithm to calculate the pose of the object. We assume that... 

The main focus of this paper was on the pose estimation problem, which was to determine the position and object models, an algorithm based on a triangulation scheme was developed. The position of the object coordinate frame was found using a nonlinear kast-squares technique. Some of the problems with the software are the fact that only the position of the object is calculated versus both the position and orientation of the object, and that both the object to be grasped and the proximity sensor characteristics are modeled as spherical. This was done to make the equation development, and thus programming, simpler. 

One therefore needs a smooth density estimation techniques that is more reliable than the histogram estimates. The automatic estimation poses additional problems in that the traditional statistical techniques for estimating densities usually require the interactive selection of some smoothing parameter (such as the bin size). Some publicly available density estimators are available, but these tended to oversmooth the densities. So we tried a number of ideas based on numerical differentiation of the empirical cdf to devise a better density estimator. 

The Toxic Substances Control Act (TSCA) was enacted in 1976 to identify and control toxic chemical ha2ards to human health and the environment. One of the main provisions of TSCA was to estabUsh and maintain an inventory of all chemicals in commerce in the United States for the purpose of regulating any of the chemicals that might pose an unreasonable risk to human health or the environment. An initial inventory of chemicals was estabhshed by requiring companies to report to the United States Environmental Protection Agency (USEPA) all substances that were imported, manufactured, processed, distributed, or disposed of in the United States. Over 50,000 chemical substances were reported. PoUowing this initial inventory, introduction of all new chemical substances requires a Premanufacturing Notification (PMN) process. To be included in the PMN are the identity of the new chemical, the estimated first year and maximum production volume, manufacture and process information, a description of proposed use, potential release to the environment, possible human exposure to the new substance, and any health or environmental test data available at the time of submission. In the 10 years that TSCA has been in effect, the USEPA has received over 10,000 PMNs and up to 10% of the submissions each year are for dyes (382)... 

Substances intended solely for scientific research and development in quantities less than 100 kg per year. Substances placed on the market for process-orientated research and development with a limited number of customers registered with die notifier. The aim of die notification systems is to identify possible risks posed to people and the environment from placing new substances on the market. A notification comprises data on the chemical identity of the substance an estimate of the quantity of the substance to be placed on the EC market details of the functions and uses of the substance Table 14.12 Notification bands ... 

Different materials pose different hazards, including thermal radiation, explosion overpressure, and toxic and flammable vapor clouds. Some materials pose only one hazard, while others may pose all four. For the purposes of ranking facilities you will need to estimate the laigest area affected by the potential hazards. You can arrive at such an estimate by calculating the greatest downwind distance to a particular level of hazatd. The following thresholds are commonly applied ... 

Nevertheless, accidents and unintended chemical releases pose serious financial risks to the chemical and petrochemical industry. In 1984 there were five major accidents in the hydrocarbon-chemical industries, totaling an estimated loss of 268 million. Hundreds of lesser accidents occur yearly. The total annual cost to the industry of accidents and unintended chemical releases is difficult to quantify. It includes significant costs owing to interruption... 

Once wells have been drilled into the formation, the local properties of the reservoir rocks and fluids can be determined. To constmct a realistic model of the reservoir, its properties over its total extent— not just at the well sites—must be known. One way of estimating these properties is to match production histories at the wells with those predicted by the reservoir model. This is a classic ill-posed inverse problem that is very difficult to solve. 

The significance of the exposure levels shown in the Levels of Significant Exposure (LSE) tables and figures may differ depending on the user s perspective. Public health officials and others concerned with appropriate actions to take at hazardous waste sites may want information on levels of exposure associated with more subtle effects in humans or animals (LOAELs) or exposure levels below which no adverse effects (NOAELs) have been observed. Estimates of levels posing minimal risk to humans (minimal risk levels or MRLs) may be of interest to health professionals and citizens alike. 

Estimates of exposure levels posing minimal risk to humans (Minimal Risk Levels or MRLs) have been made for methyl parathion. An MRL is defined as an estimate of daily human exposure to a substance that is likely to be without an appreciable risk of adverse effects (noncarcinogenic) over a specified duration of exposure. MRLs are derived when reliable and sufficient data exist to identify the target organ(s) of effect or the most sensitive health effect(s) for a specific duration within a given route of exposure. MRLs are based on noncancerous health effects only and do not consider carcinogenic effects. MRLs can be derived for acute, intermediate, and chronic duration exposures for inhalation and oral routes. Appropriate methodology does not exist to develop MRLs for dermal exposure. 

Davis DL, Ahmed AK. 1998. Exposures from indoor spraying of chlorpyrifos pose greater health risks to children than currently estimated. Environ Health Perspect 106 299-301. 

TEM is still the most powerful technique to elucidate the dispersion of nano-filler in rubbery matrix. However, the conventional TEM projects three-dimensional (3D) body onto two-dimensional (2D) (x, y) plane, hence the structural information on the thickness direction (z-axis) is only obtained as an accumulated one. This lack of z-axis structure poses tricky problems in estimating 3D structure in the sample to result in more or less misleading interpretations of the structure. How to elucidate the dispersion of nano-fillers in 3D space from 2D images has not been solved until the advent of 3D-TEM technique, which combines TEM and computerized tomography technique to afford 3D structural images, incidentally called electrontomography . 

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