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

We present the software architecture of a robotic system for mapping abandoned mines. The software is capable of acquiring consistent 2D maps of large mines with many cycles, represented as Markov random fields. 3D C-space maps are acquired from local 3D range scans, which are used to identify navigable paths using A* search. Our system has been deployed in three abandoned mines, two of which inaccessible to people, where it has acquired maps of unprecedented detail and accuracy.

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An Autonomous Robotic System for Mapping Abandoned Mines

Automation of the search for and classification of Antarctic meteorites offers a unique case for early demonstration of robotics in a scenario analogous to geological exploratory missions to other planets and to the Earth's extremes. Moreover, the discovery of new meteorite samples is of great value because meteorites are the only significant source of extraterrestrial material available to scientists. In this paper we focus on the primary outcomes and technical lessons learned from the first field demonstration of autonomous search and in situ classification of Antarctic meteorites by a robot. Using a novel autonomous control architecture, specialized science sensing, combined manipulation and visual servoing, and Bayesian classification, the Nomad robot classified five indigenous meteorites during an expedition to the remote site of Elephant Moraine in January 2000. Nomad's expedition proved the rudiments of science autonomy and exemplified the merits of machine learning techniques for autonomous geological classification in real-world settings. On the other hand, the expedition showcased the difficulty in executing reliable robotic deployment of science sensors and a limited performance in the speed and coverage of autonomous search.

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Robotic Antarctic meteorite search: outcomes

The Ambler walking robot has been developed specifically for autonomous exploration of planetary and lunar surfaces. The Ambler, which maintains its body on a level trajectory while walking, has unique orthogonal legs that are stacked under the body instead of the traditional animal-like arrangement of legs around the body. The resulting stacked configuration leads to a novel circulating gait that promises to improve mobility in terrains of extreme roughness. The Ambler's level body motion, orthogonal legs, and circulating gait greatly simplify physical control, terrain model construction, and motion planning-all of which are traditional impediments to autonomous travel across rough terrain. >

Walking robot with a circulating gait

The present invention pertains to a robot for moving along uneven terrain. The robot comprises a body having an opening through which a leg can pass. There is also a device for moving the body. The moving device includes at least 3 legs, at least one of which can exhibit an overlapping gait with respect to another leg. The robot is also comprised of a device for controlling the moving device such that the body moves along the terrain in a desired path. In an alternative embodiment, the moving device includes legs, each of which can exhibit an overlapping gait with respect to another leg while moving the body. In a preferred embodiment, each leg is comprised of a shoulder that is rotatable in a θ direction. Each leg is also comprised of a pedestal which has an axis that is disposed in essentially a z direction, where the z direction is perpendicular to the θ direction. There is also a device for linking the shoulder and the pedestal such that the pedestal can be moved in an r direction to a desired r position with respect to the shoulder, where the r direction is perpendicular to the z and the θ directions. The robot moves along the terrain which it defines with the defining device by positioning each leg in a desired place determined by the controlling device and then moving the body forward to resituate itself.

Orthogonal legged walking robot

In June and July 1997, Nomad, a planetary-relevant mobile robot, traversed more than 220 kilometers across the barren Atacama Desert in Chile, exploring a landscape analogous to the surfaces of the Moon and Mars. In this unprecedented demonstration, Nomad operated both autonomously and under the control of operators thousands of kilometers away, addressing issues of robot configuration, communication, position estimation, and navigation in rugged, natural terrain. The field experiment also served to test technologies for remote geological investigation, paving the way for new exploration strategies on Earth and beyond. Finally, by combining safeguarded teleoperation with panoramic visualization and a novel user interface, the Atacama Desert Trek provided the general public a compelling interactive experience an opportunity to remotely drive an exploratory robot. Nomad's performance in the Atacama Desert Trek set new benchmark in high performance robotics operations relevant to terrestrial and planetary exploration. This paper presents an overview of the experiment, describes technologies key to Nomad's success, and discusses outcomes and implications.

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William Whittaker

Papers

An Autonomous Robotic System for Mapping Abandoned Mines

Robotic Antarctic meteorite search: outcomes

Walking robot with a circulating gait

Orthogonal legged walking robot

The Atacama Desert Trek: outcomes