Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters

Dynamic Camera Clusters (DCCs) are multi-camera systems where one or more cameras are mounted on actuated mechanisms such as a gimbal. Existing methods for DCC calibration rely on joint angle measurements to resolve the time-varying transformation between the dynamic and static camera. This information is usually provided by motor encoders, however, joint angle measurements are not always readily available on off-the-shelf mechanisms. In this paper, we present an encoderless approach for DCC calibration which simultaneously estimates the kinematic parameters of the transformation chain as well as the unknown joint angles. We also demonstrate the integration of an encoderless gimbal mechanism with a state-of-the art VIO algorithm, and show the extensions required in order to perform simultaneous online estimation of the joint angles and vehicle localization state. The proposed calibration approach is validated both in simulation and on a physical DCC composed of a 2-DOF gimbal mounted on a UAV. Finally, we show the experimental results of the calibrated mechanism integrated into the OKVIS VIO package, and demonstrate successful online joint angle estimation while maintaining localization accuracy that is comparable to a standard static multi-camera configuration.Comment: ICRA 201

Computer program developed for flowsheet calculations and process data reduction

Computer program PACER-65, is used for flowsheet calculations and easily adapted to process data reduction. Each unit, vessel, meter, and processing operation in the overall flowsheet is represented by a separate subroutine, which the program calls in the order required to complete an overall flowsheet calculation

Business intelligence gap analysis: a user, supplier and academic perspective

Business intelligence (BI) takes many different forms, as indicated by the varying definitions of BI that can be found in industry and academia. These different definitions help us understand of what BI issues are important to the main players in the field of BI; users, suppliers and academics. The goal of this research is to discover gaps and trends from the standpoints of BI users, BI suppliers and academics, and to examine their effects on business and academia. Consultants also play an important role since they can be seen as the link between users and suppliers. Two research methods are combined to accomplish this goal. We examine the BI focus of users and suppliers through a survey, and we gain insight to the BI focus of academics, vendor-neutral consultants (typical representatives like Forrester, Gartner and IDC) and vendor- specific consultants (typical representatives like IBM, Information builders, Microsoft, Oracle and SAP) through their publications. Previous studies indicate that similar article analyses often focus on academic research methods only. That means that the results so far often reveal the academic perspective. Unlike these previous studies, the perspective of this research is not limited to academics. Our results provide insight of the BI trends and BI issue ranking of BI users, suppliers, academics, vendors neutral consultants and vendor specific consultant

An Integrated XRF/XRD Instrument for Mars Exobiology and Geology Experiments

By employing an integrated x-ray instrument on a future Mars mission, data obtained will greatly augment those returned by Viking; details characterizing the past and present environment on Mars and those relevant to the possibility of the origin and evolution of life will be acquired. A combined x-ray fluorescence/x-ray diffraction (XRF/XRD) instrument was breadboarded and demonstrated to accommodate important exobiology and geology experiment objectives outlined for MESUR and future Mars missions. Among others, primary objectives for the exploration of Mars include the intense study of local areas on Mars to establish the chemical, mineralogical, and petrological character of different components of the surface material; to determine the distribution, abundance, and sources and sinks of volatile materials, including an assessment of the biologic potential, now and during past epoches; and to establish the global chemical and physical characteristics of the Martian surface. The XRF/XRD breadboard instrument identifies and quantifies soil surface elemental, mineralogical, and petrological characteristics and acquires data necessary to address questions on volatile abundance and distribution. Additionally, the breadboard is able to characterize the biogenic element constituents of soil samples providing information on the biologic potential of the Mars environment. Preliminary breadboard experiments confirmed the fundamental instrument design approach and measurement performance

Direct x-ray response of self-scanning photodiode arrays

Self-scanning photodiode arrays were tested for their ability to measure the spatial distribution of low-energy x rays in a wavelength-dispersive spectrometer. X-ray spectral sensitivity was measured with a calibrated dc source of nearly-monochromatic characteristic-x rays with photon energies in the range of 1.5 to 8 keV. Photodiode response was found to be linear with x-ray flux. Exposure to large doses of copper radiation did not affect sensitivity. A mathematical model that describes the experimental data is presented. It was found that spatial resolving power was lowered by the dispersal of photogenerated charges. This effect was investigated with collimated beams and is described with a formula that predicts the loss of diode signals. (auth

Algorithmic statistics: forty years later

Algorithmic statistics has two different (and almost orthogonal) motivations. From the philosophical point of view, it tries to formalize how the statistics works and why some statistical models are better than others. After this notion of a "good model" is introduced, a natural question arises: it is possible that for some piece of data there is no good model? If yes, how often these bad ("non-stochastic") data appear "in real life"? Another, more technical motivation comes from algorithmic information theory. In this theory a notion of complexity of a finite object (=amount of information in this object) is introduced; it assigns to every object some number, called its algorithmic complexity (or Kolmogorov complexity). Algorithmic statistic provides a more fine-grained classification: for each finite object some curve is defined that characterizes its behavior. It turns out that several different definitions give (approximately) the same curve. In this survey we try to provide an exposition of the main results in the field (including full proofs for the most important ones), as well as some historical comments. We assume that the reader is familiar with the main notions of algorithmic information (Kolmogorov complexity) theory.Comment: Missing proofs adde

Spatial heterogeneity and irreversible vegetation change in semi-arid grazing systems

Recent theoretical studies have shown that spatial redistribution of surface water may explain the occurrence of patterns of alternating vegetated and degraded patches in semiarid grasslands. These results implied, however, that spatial redistribution processes cannot explain the collapse of production on coarser scales observed in these systems. We present a spatially explicit vegetation model to investigate possible mechanisms explaining irreversible vegetation collapse on coarse spatial scales. The model results indicate that the dynamics of vegetation on coarse scales are determined by the interaction of two spatial feedback processes. Loss of plant cover in a certain area results in increased availability of water in remaining vegetated patches through run-on of surface water, promoting within-patch plant production. Hence, spatial redistribution of surface water creates negative feedback between reduced plant cover and increased plant growth in remaining vegetation. Reduced plant cover, however, results in focusing of herbivore grazing in the remaining vegetation. Hence, redistribution of herbivores creates positive feedback between reduced plant cover and increased losses due to grazing in remaining vegetated patches, leading to collapse of the entire vegetation. This may explain irreversible vegetation shifts in semiarid grasslands on coarse spatial scales