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

Logistics outsourcing and 3PL selection: A Case study in an automotive supply chain

Outsourcing logistics functions to third-party logistics (3PL) providers has been a source of competitive advantage for most companies. Companies cite greater flexibility, operational efficiency, improved customer service levels, and a better focus on their core businesses as part of the advantages of engaging the services of 3PL providers. There are few complete and structured methodologies for selecting a 3PL provider. This paper discusses how one such methodology, namely the Analytic Hierarchy Process (AHP), is used in an automotive supply chain for export parts to redesign the logistics operations and to select a global logistics service provider

Sensor enclosures: example application and implications for data coherence

Sensors deployed in natural environments, such as rivers, beaches and glaciers, experience large forces and damaging environmental conditions. Sensors need to be robust, securely operate for extended time periods and be readily relocated and serviced. The sensors must be housed in materials that mimic natural conditions of size, density, shape and roughness. We have developed an encasement system for sensors required to measure large forces experienced by mobile river sediment grains. Sensors are housed within two discrete cases that are rigidly conjoined. The inner case exactly fits the sensor, radio components and power source. This case can be mounted within outer cases of any larger size and can be precisely moulded to match the shapes of natural sediment. Total grain mass can be controlled by packing the outer case with dense material. Case design uses Solid-WorksTM software, and shape-matching involved 3D laser scanning of natural pebbles. The cases were printed using a HP DesignjetTM 3D printer that generates high precision parts that lock rigidly in place. The casings are watertight and robust. Laboratory testing produces accurate results over a wider range of accelerations than previously reported

Measurement in marketing

We distinguish three senses of the concept of measurement (measurement as the selection of observable indicators of theoretical concepts, measurement as the collection of data from respondents, and measurement as the formulation of measurement models linking observable indicators to latent factors representing the theoretical concepts), and we review important issues related to measurement in each of these senses. With regard to measurement in the first sense, we distinguish the steps of construct definition and item generation, and we review scale development efforts reported in three major marketing journals since 2000 to illustrate these steps and derive practical guidelines. With regard to measurement in the second sense, we look at the survey process from the respondent's perspective and discuss the goals that may guide participants' behavior during a survey, the cognitive resources that respondents devote to answering survey questions, and the problems that may occur at the various steps of the survey process. Finally, with regard to measurement in the third sense, we cover both reflective and formative measurement models, and we explain how researchers can assess the quality of measurement in both types of measurement models and how they can ascertain the comparability of measurements across different populations of respondents or conditions of measurement. We also provide a detailed empirical example of measurement analysis for reflective measurement models