Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

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Computer Vision: Algorithms and Applications

We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera

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MonoSLAM: Real-Time Single Camera SLAM

This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method. While there are still many practical issues to overcome, especially in more complex outdoor environments, the general SLAM method is now a well understood and established part of robotics. Another part of the tutorial summarized more recent works in addressing some of the remaining issues in SLAM, including computation, feature representation, and data association

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Simultaneous localization and mapping: part I

A system and method detects obstacles in a road being traveled by a vehicle. Edge points of the road are calculated from known road data. A series of scan lines are made of the road ahead of the vehicle to obtain an image plane of the road ahead of the vehicle. The calculated edge points are projected into the image plane to determine the left and right edge points of each scan line in the image plane. Each scan line is processed to locate any discontinuities between the left and right edge points, where the discontinuities correspond to objects in the road.

System and method for detecting obstacles in a road

During the Summer of 1997, Nomad, a planetary-relevant mobile robot, was driven via satellite link for more than 125 miles in the Atacama Desert of Chile by novice operators in North America, demonstrating many technologies relevant to robotic exploration of the planets. An innovative "transforming" chassis was demonstrated which uses a simple linkage to change the footprint of the vehicle from a stowed to a deployed position. This linkage also enables both double Ackennan and point-turn steering. This paper presents details on the design of the transforming chassis including kinematic analysis used in low and high level control.

Nomad: a demonstration of the transforming chassis

The Robotic Antarctic Meteorite Search at Carnegie Mellon is developing robotic technologies to allow for autonomous search and classification of meteorites in Antarctica. In November 1998, the robot Nomad was deployed in the Patriot Hills region of Antarctica to perform several demonstrations and experiments of these technologies in a polar environment. Nomad drove 10.3km autonomously in Antarctica under a variety of weather and terrain conditions. This paper presents the results of this traverse, the ability of stereo vision and laser scanner to perceive polar terrain and the autonomous navigation system used.

Autonomous Navigation Field Results of a Planetary Analog Robot in Antarctica

Scarab is a demonstration of a lunar rover design to explore polar cold traps for water ice as a potential resource. The envisioned mission scenario lands the rover on the floor of a permanently shadowed crater. The radioisotope powered rover then traverses kilometers in darkness, stopping to drill into the near subsurface and take data. The vehicle design employs a passive kinematic suspension with an active adjustability to lower for drilling and aid in driving. Scarab was designed and built in 2007 and is currently in lab and field testing and further development.

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William Whittaker

Papers

System and method for detecting obstacles in a road

Nomad: a demonstration of the transforming chassis

Autonomous Navigation Field Results of a Planetary Analog Robot in Antarctica

Design of the Scarab Rover for Mobility & Drilling in the Lunar Cold Traps

Second Experiments in the Robotic Investigation of Life in the Atacama Desert of Chile