A Multi-Sensor Fusion-Based Underwater Slam System

This dissertation addresses the problem of real-time Simultaneous Localization and Mapping (SLAM) in challenging environments. SLAM is one of the key enabling technologies for autonomous robots to navigate in unknown environments by processing information on their on-board computational units. In particular, we study the exploration of challenging GPS-denied underwater environments to enable a wide range of robotic applications, including historical studies, health monitoring of coral reefs, underwater infrastructure inspection e.g., bridges, hydroelectric dams, water supply systems, and oil rigs. Mapping underwater structures is important in several fields, such as marine archaeology, Search and Rescue (SaR), resource management, hydrogeology, and speleology. However, due to the highly unstructured nature of such environments, navigation by human divers could be extremely dangerous, tedious, and labor intensive. Hence, employing an underwater robot is an excellent fit to build the map of the environment while simultaneously localizing itself in the map. The main contribution of this dissertation is the design and development of a real-time robust SLAM algorithm for small and large scale underwater environments. SVIn – a novel tightly-coupled keyframe-based non-linear optimization framework fusing Sonar, Visual, Inertial and water depth information with robust initialization, loop-closing, and relocalization capabilities has been presented. Introducing acoustic range information to aid the visual data, shows improved reconstruction and localization. The availability of depth information from water pressure enables a robust initialization and refines the scale factor, as well as assists to reduce the drift for the tightly-coupled integration. The complementary characteristics of these sensing v modalities provide accurate and robust localization in unstructured environments with low visibility and low visual features – as such make them the ideal choice for underwater navigation. The proposed system has been successfully tested and validated in both benchmark datasets and numerous real world scenarios. It has also been used for planning for underwater robot in the presence of obstacles. Experimental results on datasets collected with a custom-made underwater sensor suite and an autonomous underwater vehicle (AUV) Aqua2 in challenging underwater environments with poor visibility, demonstrate performance never achieved before in terms of accuracy and robustness. To aid the sparse reconstruction, a contour-based reconstruction approach utilizing the well defined edges between the well lit area and darkness has been developed. In particular, low lighting conditions, or even complete absence of natural light inside caves, results in strong lighting variations, e.g., the cone of the artificial video light intersecting underwater structures and the shadow contours. The proposed method utilizes these contours to provide additional features, resulting into a denser 3D point cloud than the usual point clouds from a visual odometry system. Experimental results in an underwater cave demonstrate the performance of our system. This enables more robust navigation of autonomous underwater vehicles using the denser 3D point cloud to detect obstacles and achieve higher resolution reconstructions

Parallelizing Sequential Programs With Statistical Accuracy Tests

We present QuickStep, a novel system for parallelizing sequential programs. QuickStep deploys a set of parallelization transformations that together induce a search space of candidate parallel programs. Given a sequential program, representative inputs, and an accuracy requirement, QuickStep uses performance measurements, profiling information, and statistical accuracy tests on the outputs of candidate parallel programs to guide its search for a parallelizationthat maximizes performance while preserving acceptable accuracy. When the search completes, QuickStep produces an interactive report that summarizes the applied parallelization transformations, performance, and accuracy results for the automatically generated candidate parallel programs. In our envisioned usage scenarios, the developer examines this report to evaluate the acceptability of the final parallelization and to obtain insight into how the original sequential program responds to different parallelization strategies. Itis also possible for the developer (or even a user of the program who has no software development expertise whatsoever) to simply use the best parallelization out of the box without examining the report or further investigating the parallelization. Results from our benchmark set of applications show that QuickStep can automatically generate accurate and efficient parallel programs---the automatically generated parallel versions of five of our six benchmark applications run between 5.0 and 7.7 times faster on 8 cores than the original sequential versions. Moreover, a comparison with the Intel icc compiler highlights how QuickStep can effectively parallelize applications with features (such as the use of modern object-oriented programming constructs or desirable parallelizations with infrequent but acceptable data races) that place them inherently beyond the reach of standard approaches

Analysis and evaluation of embedded graphics solutions for critical systems

En el camp dels sistemes crítics, que inclou l'automotriu, l'aviònica i els sistemes espacials, es necessita més capacitat de computació per aportar tant valor funcional com seguretat addicional. Per aconseguir-ho, la indústria està considerant noves arquitectures per futurs sistemes crítics. Una de les possibles opcions és l'ús de targetes gràfiques mòbils, que tenen un rendiment excel·lent per tasques computacionals complexes i un baix nivell de consum. Per desgràcia, les eines actuals de desenvolupament per programació de propòsit general de targetes gràfiques com CUDA o OpenCL no compleixen amb les regulacions dels estàndards de seguretat dels sistemes crítics segurs. Per altra banda, hi ha altres solucions per programar per gràfics, com ara OpenGL SC 2 i Brook Auto, que són fàcils de certificar. En aquest projecte, analitzem aquestes solucions per programar per targetes gràfiques i explorem els diferents aspectes del desenvolupament de programari de propòsit general amb elles. Us presentem la nostra experiència adaptant codi de dues aplicacions de dos sectors diferents de sistemes crítics, l'aviònica i els sistemes espacials, a diferents \textit{APIs} (OpenGL 2, OpenGL ES 2, OpenGL SC 2 i Brook Auto) i l'avaluació de les versions que nosaltres hem generat. En funcionalitat i rendiment, no s'ha observat cap diferència, tot i que sí que hem notat un gran salt comparatiu en la complexitat del desenvolupament i la productivitat entre eines orientades només a sistemes gràfics i Brook Auto.In the safety-critical systems domain, which includes automotive, avionics and space systems, more compute power is needed to provide additional functional value and safety. In order to achieve this, new hardware architectures are considered from industry for future critical systems. One of this approaches is the use of mobile GPUs, which have excellent performance capabilities for intensive computational tasks and low-power consumption. However, current programming models for general purpose programming of GPUs like CUDA and OpenCL do not comply with the safety standards of safety critical systems. On the other hand, there are alternative programming solutions based on graphics, namely OpenGL SC 2 and Brook Auto, which are certification-friendly. In this thesis, we perform an analysis of these safety-critical programming models for GPUs and we explore the different aspects of the development of general purpose software in them. We present our experience with porting two applications from two distinct safety-critical domains, aerospace and avionics, in several graphics-based APIs (OpenGL 2, OpenGL ES 2, OpenGL SC 2 and Brook Auto) and the evaluation of our produced versions. In terms of functionality and performance, no difference has been observed, whereas we noticed a big gap in the development complexity and productivity between pure graphics solutions and Brook Auto

Women Give 2014

In America today fewer individuals are affiliating with organized religion; in fact, one-third of Americans under 30 have no religious affiliation. For those concerned that the falling rate of religious affiliation will have an adverse effect on individual charitable giving, Women Give 2014 finds encouraging results

The EMCC / DARPA Massively Parallel Electromagnetic Scattering Project

The Electromagnetic Code Consortium (EMCC) was sponsored by the Advanced Research Program Agency (ARPA) to demonstrate the effectiveness of massively parallel computing in large scale radar signature predictions. The EMCC/ARPA project consisted of three parts