Perception-aware Path Planning

In this paper, we give a double twist to the problem of planning under uncertainty. State-of-the-art planners seek to minimize the localization uncertainty by only considering the geometric structure of the scene. In this paper, we argue that motion planning for vision-controlled robots should be perception aware in that the robot should also favor texture-rich areas to minimize the localization uncertainty during a goal-reaching task. Thus, we describe how to optimally incorporate the photometric information (i.e., texture) of the scene, in addition to the the geometric one, to compute the uncertainty of vision-based localization during path planning. To avoid the caveats of feature-based localization systems (i.e., dependence on feature type and user-defined thresholds), we use dense, direct methods. This allows us to compute the localization uncertainty directly from the intensity values of every pixel in the image. We also describe how to compute trajectories online, considering also scenarios with no prior knowledge about the map. The proposed framework is general and can easily be adapted to different robotic platforms and scenarios. The effectiveness of our approach is demonstrated with extensive experiments in both simulated and real-world environments using a vision-controlled micro aerial vehicle.Comment: 16 pages, 20 figures, revised version. Conditionally accepted for IEEE Transactions on Robotic

Water Absorption Properties of Cement Pastes: Experimental and Modelling Inspections

An intermingled fractal units’ model is shown in order to simulate pore microstructures as pore fraction and pore size distribution. This model is aimed at predicting capillary water absorption coefficient and sorptivity values in cement pastes. The results obtained are in good agreement with the experimental ones. For validating this model, a comparison with other procedures has been shown. It is possible to establish that the newly proposed method matches better with the experimental results. That is probably due to the fact that pore size distribution has been considered as a whole. Moreover, even though the proposed model is based on fractal base units, it is able to simulate and predict different properties as well as nonfractal porous microstructure

Talbot effect for dispersion in linear optical fibers and a wavelet approach

We shortly recall the mathematical and physical aspects of Talbot's self-imaging effect occurring in near-field diffraction. In the rational paraxial approximation, the Talbot images are formed at distances z=p/q, where p and q are coprimes, and are superpositions of q equally spaced images of the original binary transmission (Ronchi) grating. This interpretation offers the possibility to express the Talbot effect through Gauss sums. Here, we pay attention to the Talbot effect in the case of dispersion in optical fibers presenting our considerations based on the close relationships of the mathematical representations of diffraction and dispersion. Although dispersion deals with continuous functions, such as gaussian and supergaussian pulses, whereas in diffraction one frequently deals with discontinuous functions, the mathematical correspondence enables one to characterize the Talbot effect in the two cases with minor differences. In addition, we apply, for the first time to our knowledge, the wavelet transform to the fractal Talbot effect in both diffraction and fiber dispersion. In the first case, the self similar character of the transverse paraxial field at irrational multiples of the Talbot distance is confirmed, whereas in the second case it is shown that the field is not self similar for supergaussian pulses. Finally, a high-precision measurement of irrational distances employing the fractal index determined with the wavelet transform is pointed outComment: 15 text pages + 7 gif figs, accepted at Int. J. Mod. Phys. B, final version of a contribution at ICSSUR-Besancon (May/05). Color figs available from the first autho

Carbon Nanotube Field Emission Arrays

This effort exploits the unique physical and electrical characteristics of carbon nanotubes (CNTs) for field emission applications. Carbon nanotube field emission devices are designed, fabricated, and tested. Two reliable CNT synthesis methods, microwave plasma enhanced chemical vapor deposition (MPE-CVD) and thermal chemical vapor deposition (T-CVD), are developed. The physical properties of the resulting CNTs are analyzed using Raman spectroscopy and Scanning electron microscopy (SEM) and then tested for field emission performance. The T-CVD grown CNTs are shown to have fewer growth defects, but suffer from less process control making integration into devices difficult without further process development. Field emission testing shows the T-CVD CNTs to be much better emitters, exceeding 13 mA/cm2 at an electric field of only 1.4 V/micrometer, while the best MPE-CVD CNTs only managed 1 mA/cm2 at the much higher electric field of 4.56 V/micrometer. Two methods of device fabrication, conventional photolithography and nanosphere lithography, are developed and used to fabricate gated field emission arrays. Finite element analysis is used to optimize the gated array design to maximize the electric field strength. All fabrication steps are successfully demonstrated and prototype devices tested and compared to simple CNT carpet samples showing marked improvements by reducing electrostatic screening effects