25,597 research outputs found

    Keyframe-based monocular SLAM: design, survey, and future directions

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    Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery

    Non-linear Kalman filters for calibration in radio interferometry

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    We present a new calibration scheme based on a non-linear version of Kalman filter that aims at estimating the physical terms appearing in the Radio Interferometry Measurement Equation (RIME). We enrich the filter's structure with a tunable data representation model, together with an augmented measurement model for regularization. We show using simulations that it can properly estimate the physical effects appearing in the RIME. We found that this approach is particularly useful in the most extreme cases such as when ionospheric and clock effects are simultaneously present. Combined with the ability to provide prior knowledge on the expected structure of the physical instrumental effects (expected physical state and dynamics), we obtain a fairly cheap algorithm that we believe to be robust, especially in low signal-to-noise regime. Potentially the use of filters and other similar methods can represent an improvement for calibration in radio interferometry, under the condition that the effects corrupting visibilities are understood and analytically stable. Recursive algorithms are particularly well adapted for pre-calibration and sky model estimate in a streaming way. This may be useful for the SKA-type instruments that produce huge amounts of data that have to be calibrated before being averaged

    Robust Estimation and Wavelet Thresholding in Partial Linear Models

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    This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component, and unobservable Gaussian distributed random errors. We present a wavelet thresholding based estimation procedure to estimate the components of the partial linear model by establishing a connection between an l1l_1-penalty based wavelet estimator of the nonparametric component and Huber's M-estimation of a standard linear model with outliers. Some general results on the large sample properties of the estimates of both the parametric and the nonparametric part of the model are established. Simulations and a real example are used to illustrate the general results and to compare the proposed methodology with other methods available in the recent literature

    Optimal Dark Hole Generation via Two Deformable Mirrors with Stroke Minimization

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    The past decade has seen a significant growth in research targeted at space based observatories for imaging exo-solar planets. The challenge is in designing an imaging system for high-contrast. Even with a perfect coronagraph that modifies the point spread function to achieve high-contrast, wavefront sensing and control is needed to correct the errors in the optics and generate a "dark hole". The high-contrast imaging laboratory at Princeton University is equipped with two Boston Micromachines Kilo-DMs. We review here an algorithm designed to achieve high-contrast on both sides of the image plane while minimizing the stroke necessary from each deformable mirror (DM). This algorithm uses the first DM to correct for amplitude aberrations and the second DM to create a flat wavefront in the pupil plane. We then show the first results obtained at Princeton with this correction algorithm, and we demonstrate a symmetric dark hole in monochromatic light

    LiDAR-derived digital holograms for automotive head-up displays.

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    A holographic automotive head-up display was developed to project 2D and 3D ultra-high definition (UHD) images using LiDAR data in the driver's field of view. The LiDAR data was collected with a 3D terrestrial laser scanner and was converted to computer-generated holograms (CGHs). The reconstructions were obtained with a HeNe laser and a UHD spatial light modulator with a panel resolution of 3840×2160 px for replay field projections. By decreasing the focal distance of the CGHs, the zero-order spot was diffused into the holographic replay field image. 3D holograms were observed floating as a ghost image at a variable focal distance with a digital Fresnel lens into the CGH and a concave lens.This project was funded by the EPSRC Centre for Doctoral Training in Connected Electronic and Photonic Systems (CEPS) (EP/S022139/1), Project Reference: 2249444

    Bayesian Cosmic Web Reconstruction: BARCODE for Clusters

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    We describe the Bayesian BARCODE formalism that has been designed towards the reconstruction of the Cosmic Web in a given volume on the basis of the sampled galaxy cluster distribution. Based on the realization that the massive compact clusters are responsible for the major share of the large scale tidal force field shaping the anisotropic and in particular filamentary features in the Cosmic Web. Given the nonlinearity of the constraints imposed by the cluster configurations, we resort to a state-of-the-art constrained reconstruction technique to find a proper statistically sampled realization of the original initial density and velocity field in the same cosmic region. Ultimately, the subsequent gravitational evolution of these initial conditions towards the implied Cosmic Web configuration can be followed on the basis of a proper analytical model or an N-body computer simulation. The BARCODE formalism includes an implicit treatment for redshift space distortions. This enables a direct reconstruction on the basis of observational data, without the need for a correction of redshift space artifacts. In this contribution we provide a general overview of the the Cosmic Web connection with clusters and a description of the Bayesian BARCODE formalism. We conclude with a presentation of its successful workings with respect to test runs based on a simulated large scale matter distribution, in physical space as well as in redshift space.Comment: 18 pages, 8 figures, Proceedings of IAU Symposium 308 "The Zeldovich Universe: Genesis and Growth of the Cosmic Web", 23-28 June 2014, Tallinn, Estoni
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