On-Manifold Preintegration for Real-Time Visual-Inertial Odometry

Current approaches for visual-inertial odometry (VIO) are able to attain highly accurate state estimation via nonlinear optimization. However, real-time optimization quickly becomes infeasible as the trajectory grows over time, this problem is further emphasized by the fact that inertial measurements come at high rate, hence leading to fast growth of the number of variables in the optimization. In this paper, we address this issue by preintegrating inertial measurements between selected keyframes into single relative motion constraints. Our first contribution is a \emph{preintegration theory} that properly addresses the manifold structure of the rotation group. We formally discuss the generative measurement model as well as the nature of the rotation noise and derive the expression for the \emph{maximum a posteriori} state estimator. Our theoretical development enables the computation of all necessary Jacobians for the optimization and a-posteriori bias correction in analytic form. The second contribution is to show that the preintegrated IMU model can be seamlessly integrated into a visual-inertial pipeline under the unifying framework of factor graphs. This enables the application of incremental-smoothing algorithms and the use of a \emph{structureless} model for visual measurements, which avoids optimizing over the 3D points, further accelerating the computation. We perform an extensive evaluation of our monocular \VIO pipeline on real and simulated datasets. The results confirm that our modelling effort leads to accurate state estimation in real-time, outperforming state-of-the-art approaches.Comment: 20 pages, 24 figures, accepted for publication in IEEE Transactions on Robotics (TRO) 201

Structure and function of the membrane protein Opa60 by solid-state NMR

Studying the structure of transmembrane (TM) proteins is an important task since many of them are drug targets and are involved in essential cellular functions. However, new techniques are urgently needed, as TM proteins are not amenable to conventional techniques. The recent development of ultrafast magic angle spinning solid-state NMR with proton detection provides a promising avenue. The protein Opa60 is a β-barrel TM protein found in the outer membrane of the human pathogen Neisseria gonorrhoeae and mediates adhesion to human host cells via the hCEACAM-family of TM proteins with its large extracellular loops. Its structure has been determined previously in detergent micelles by solution NMR. However, structural insight in a native-like environment is needed to study the binding of Opa60 to its receptor under more physiological conditions and therefore, proton-detected solid-state NMR was chosen in this thesis as a technique to study Opa60 in DMPC lipid bilayers. In this work, the structure of the β-barrel was successfully determined and shows an extension of the length of the β-strands compared to the solution structure. The loops retain their dynamic behavior and are not visible in cross polarization based solid-state NMR experiments. The binding of Opa60 to the N-terminal domain of hCEACAM1 (hCEACAM1-N) could not be shown in lipid bilayers, however solution NMR data indicated a possible interaction in detergent. Opa60 in DMPC was compared with Opa60 in two different LPS species and Kdo2-lipid A, which resemble the native outer membrane environment of N. gonorrhoeae, but no major structural changes were apparent from the spectra. In the future, the assignments should be completed and likely reveal the extension of the complete β-barrel to match the thickness of the lipid bilayer. The receptor binding conditions will need to be investigated systematically. Alternatively, a solution NMR assignment of hCEACAM1-N can be conducted and used as a starting point to target the binding surface of Opa60 employing various isotopic labeling schemes. Method development in solid-state NMR is ongoing and of high importance. Techniques for accurate internuclear distance determination are sought for. In this thesis, a new technique was developed termed TRansferred Rotational DOuble Resonance (TREDOR), based on the TEDOR and REDOR sequences. In TREDOR, both starting and transferred signal are co-acquired and this enables a single parameter fit to the internuclear distance. After calibrating the fitting, the accuracy and ease of TREDOR was demonstrated on the microcrystalline protein SH3. The structure was determined using only TREDOR-derived distances and TALOS-N angle restraints. The superiority of TREDOR over TEDOR was shown in terms of distance accuracy when compared to a known crystal structure of SH3. Moreover, TREDOR can be applied with only a single mixing time, drastically reducing the necessary measurement time. TREDOR was applied to the TM protein Opa60, and one long-distance contact was found. The technique is mostly limited by strong peak overlap, as seen for Opa60. The application of TREDOR to other challenging systems will likely prove it to be a valuable tool in structural biology.2021-10-2

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

Banking consolidation and small businessfinance: empirical evidence for Germany

Since the early 1990s an unprecedented process of consolidation has taken place in the banking sector in most industrialised countries raising concern of policymakers that it may reduce access to credit for the small business sector. While most of the existing empirical studies have focused on the U.S., this paper is the first one empirically investigating the effects of banking consolidation in Germany. As small and medium sized German companies traditionally almost exclusively rely on bank credit and as they represent the vast majority of the corporate sector reduced credit availability for those companies could particularly endanger economic growth. Based on an exceptional panel dataset comprising merged data of the German credit register and balance sheet data of German firms and banks we find - contrary to public fear - that the ongoing banking consolidation in Germany does not have a significant negative impact on the financing of small and medium-sized enterprises (SME). We measure the financing opportunities of SMEs based on the bank debt/assets ratio and the logarithmized credit size and control both explicitly for bank mergers and for the increase in the average bank size in the course of the consolidation process. In addition, we observe that the concentration in the banking market is insignificant for SME financing and that there is no significant difference between commercial banks, savings banks and private banks. --Banking consolidation,bank mergers,SME financing

Cosmological Implications of the Second Parameter of Type Ia Supernovae

Theoretical models predict that the initial metallicity of the progenitor of a Type Ia supernova (SN Ia) affects the peak of the supernova light curve. This can cause a deviation from the standard light curve calibration employed when using SNe Ia as standardizable distance candles and, if there is a systematic evolution of the metallicity of SN Ia progenitors, could affect the determination of cosmological parameters. Here we show that this metallicity effect can be substantially larger than has been estimated previously, when the neutronisation in the immediate pre-explosion phase in the CO white dwarf is taken into account, and quantitatively assess the importance of metallicity evolution for determining cosmological parameters. We show that, in principle, a moderate and plausible amount of metallicity evolution could mimic a lambda-dominated, flat Universe in an open, lambda-free Universe. However, the effect of metallicity evolution appears not large enough to explain the high-z SN Ia data in a flat Universe, for which there is strong independent evidence, without a cosmological constant. We also estimate the systematic uncertainties introduced by metallicity evolution in a lambda-dominated, flat Universe. We find that metallicity evolution may limit the precision with which Omega_m and w can be measured and that it will be difficult to distinguish evolution of the equation of state of dark energy from metallicity evolution, at least from SN Ia data alone.Comment: 10 pages, 6 figures, constructive comments welcom

Exploiting XML Technologies in Medical Information Systems

Integration of clinical research data and routine care data, in order to streamline the process of conducting clinical studies, has been a problem for quite a while now. The Single Source project at the University of Münster aims at contributing to this area. The approach is based on a vast usage of XML technology together with a novel integration architecture. The emphasis in this paper is on the former: The seamless usage of XML technology throughout the entire application is presented, and mismatches of programming paradigms are averted by exploiting the features of XML, XQuery and XForms. In particular, this is demonstrated by the example of a component used for handling forms, by how it is built and used in the entire scenario

Productivity and Profitability of a Cotton-based Production System under Organic and Conventional Management in India

The debate on the relative benefits of conventional and organic farming systems is more topical than ever. The achievements of conventional high-input agriculture were largely brought about at the cost of deteriorating soil fertility; furthermore, they were based to a large extent on fossil fuels. Developing more sustainable farming practices on a large scale is of utmost importance. However, information about the performance of agricultural production systems under organic and conventional management in tropical and subtropical regions is largely lacking. This study aimed to assess agronomic and economic data from a long-term farming systems comparison trial under semi-arid conditions in central India. Four two-year crop rotations comprising cotton-soybean-wheat under biodynamic, organic and conventional management were investigated, including one conventional system with and one without transgenic Bt cotton, between 2007 and 2010. Results showed 13% lower yields in organic compared to conventional systems. Yields in cotton, soybean and wheat were on average 14 %, 7% and 15% lower, respectively. However, production costs of organic systems were on average 32% lower than those of conventional systems, which led to similar gross margins in all systems. To our knowledge, this is the first long-term field trial comparing the agronomic and economic performance of organic, conventional and conventional+Bt cotton-based farming systems. The results of our study suggest that organic farming is a promising alternative to conventional farming in cotton-based production systems in central India. The less capital intensive nature of organic systems may be particularly interesting for smallholder farmers as it decreases dependence on loans for farm inputs. Therefore, our findings have the potential to be useful for decision-making and in turn may lead to a redirection of agricultural policies

Competition of languages in the presence of a barrier

Using the Schulze model for Monte Carlo simulations of language competition, we include a barrier between the top half and the bottom half of the lattice. We check under which conditions two different languages evolve as dominating in the two halves.Comment: 6 pages including 3 figure