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Author: Simon Rohou Publisher: John Wiley & Sons ISBN: 1848219709 Category : Technology & Engineering Languages : en Pages : 293
Book Description
Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.
Author: Simon Rohou Publisher: John Wiley & Sons ISBN: 1848219709 Category : Technology & Engineering Languages : en Pages : 293
Book Description
Localization for underwater robots remains a challenging issue. Typical sensors, such as Global Navigation Satellite System (GNSS) receivers, cannot be used under the surface and other inertial systems suffer from a strong integration drift. On top of that, the seabed is generally uniform and unstructured, making it difficult to apply Simultaneous Localization and Mapping (SLAM) methods to perform localization. Reliable Robot Localization presents an innovative new method which can be characterized as a raw-data SLAM approach. It differs from extant methods by considering time as a standard variable to be estimated, thus raising new opportunities for state estimation, so far underexploited. However, such temporal resolution is not straightforward and requires a set of theoretical tools in order to achieve the main purpose of localization. This book not only presents original contributions to the field of mobile robotics, it also offers new perspectives on constraint programming and set-membership approaches. It provides a reliable contractor programming framework in order to build solvers for dynamical systems. This set of tools is illustrated throughout this book with realistic robotic applications.
Author: Hanafiah Yussof Publisher: BoD – Books on Demand ISBN: 9537619834 Category : Computers Languages : en Pages : 589
Book Description
Localization and mapping are the essence of successful navigation in mobile platform technology. Localization is a fundamental task in order to achieve high levels of autonomy in robot navigation and robustness in vehicle positioning. Robot localization and mapping is commonly related to cartography, combining science, technique and computation to build a trajectory map that reality can be modelled in ways that communicate spatial information effectively. This book describes comprehensive introduction, theories and applications related to localization, positioning and map building in mobile robot and autonomous vehicle platforms. It is organized in twenty seven chapters. Each chapter is rich with different degrees of details and approaches, supported by unique and actual resources that make it possible for readers to explore and learn the up to date knowledge in robot navigation technology. Understanding the theory and principles described in this book requires a multidisciplinary background of robotics, nonlinear system, sensor network, network engineering, computer science, physics, etc.
Author: David Israel González Aguirre Publisher: Springer ISBN: 3319978411 Category : Technology & Engineering Languages : en Pages : 220
Book Description
This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental questions: What & where is it? To answer these questions using a sensor-to-representation bridge, coordinated processes are conducted to extract and exploit cues matching robot’s mental representations to physical entities. These include sensor & actuator modeling, calibration, filtering, and feature extraction for state estimation. This book discusses the following topics in depth: • Active Sensing: Robust probabilistic methods for optimal, high dynamic range image acquisition are suitable for use with inexpensive cameras. This enables ideal sensing in arbitrary environmental conditions encountered in human-centric spaces. The book quantitatively shows the importance of equipping robots with dependable visual sensing. • Feature Extraction & Recognition: Parameter-free, edge extraction methods based on structural graphs enable the representation of geometric primitives effectively and efficiently. This is done by eccentricity segmentation providing excellent recognition even on noisy & low-resolution images. Stereoscopic vision, Euclidean metric and graph-shape descriptors are shown to be powerful mechanisms for difficult recognition tasks. • Global Self-Localization & Depth Uncertainty Learning: Simultaneous feature matching for global localization and 6D self-pose estimation are addressed by a novel geometric and probabilistic concept using intersection of Gaussian spheres. The path from intuition to the closed-form optimal solution determining the robot location is described, including a supervised learning method for uncertainty depth modeling based on extensive ground-truth training data from a motion capture system. The methods and experiments are presented in self-contained chapters with comparisons and the state of the art. The algorithms were implemented and empirically evaluated on two humanoid robots: ARMAR III-A & B. The excellent robustness, performance and derived results received an award at the IEEE conference on humanoid robots and the contributions have been utilized for numerous visual manipulation tasks with demonstration at distinguished venues such as ICRA, CeBIT, IAS, and Automatica.
Author: Jose A. Castellanos Publisher: Springer Science & Business Media ISBN: 146154405X Category : Technology & Engineering Languages : en Pages : 212
Book Description
During the last decade, many researchers have dedicated their efforts to constructing revolutionary machines and to providing them with forms of artificial intelligence to perform some of the most hazardous, risky or monotonous tasks historically assigned to human beings. Among those machines, mobile robots are undoubtedly at the cutting edge of current research directions. A rough classification of mobile robots can be considered: on the one hand, mobile robots oriented to human-made indoor environments; on the other hand, mobile robots oriented to unstructured outdoor environments, which could include flying oriented robots, space-oriented robots and underwater robots. The most common motion mechanism for surface mobile robots is the wheel-based mechanism, adapted both to flat surfaces, found in human-made environments, and to rough terrain, found in outdoor environments. However, some researchers have reported successful developments with leg-based mobile robots capable of climbing up stairs, although they require further investigation. The research work presented here focuses on wheel-based mobile robots that navigate in human-made indoor environments. The main problems described throughout this book are: Representation and integration of uncertain geometric information by means of the Symmetries and Perturbations Model (SPmodel). This model combines the use of probability theory to represent the imprecision in the location of a geometric element, and the theory of symmetries to represent the partiality due to characteristics of each type of geometric element. A solution to the first location problem, that is, the computation of an estimation for the mobile robot location when the vehicle is completely lost in the environment. The problem is formulated as a search in an interpretation tree using efficient matching algorithms and geometric constraints to reduce the size of the solution space. The book proposes a new probabilistic framework adapted to the problem of simultaneous localization and map building for mobile robots: the Symmetries and Perturbations Map (SPmap). This framework has been experimentally validated by a complete experiment which profited from ground-truth to accurately validate the precision and the appropriateness of the approach. The book emphasizes the generality of the solutions proposed to the different problems and their independence with respect to the exteroceptive sensors mounted on the mobile robot. Theoretical results are complemented by real experiments, where the use of multisensor-based approaches is highlighted.
Author: Ansgar Bredenfeld Publisher: Springer Science & Business Media ISBN: 3540354379 Category : Technology & Engineering Languages : en Pages : 742
Book Description
This book constitutes the ninth official archival publication devoted to RoboCup, documenting presentations at the RoboCup 2005 International Symposium, held in Osaka, Japan, July 2005 alongside the RoboCup Competition. The book presents 34 revised full papers and 38 revised short papers together with two award-winning papers. This is a valuable source of reference and inspiration for those interested in robotics or distributed intelligence, and mandatory reading for the rapidly growing RoboCup community.
Author: Anna V. Petrovskaya Publisher: Stanford University ISBN: Category : Languages : en Pages : 226
Book Description
Reliable perception is required in order for robots to operate safely in unpredictable and complex human environments. However, reliability of perceptual inference algorithms has been poorly studied so far. These algorithms capture uncertain knowledge about the world in the form of probabilistic belief distributions. A number of Monte Carlo and deterministic approaches have been developed, but their efficiency depends on the degree of smoothness of the beliefs. In the real world, the smoothness assumption often fails, leading to unreliable perceptual inference results. Motivated by concrete robotics problems, we propose two novel perceptual inference algorithms that explicitly consider local non-smoothness of beliefs and adapt to it. Both of these algorithms fall into the category of iterative divide-and-conquer methods and hence scale logarithmically with desired accuracy. The first algorithm is termed Scaling Series. It is an iterative Monte Carlo technique coupled with annealing. Local non-smoothness is accounted for by sampling strategy and by annealing schedule. The second algorithm is termed GRAB, which stands for Guaranteed Recursive Adaptive Bounding. GRAB is an iterative adaptive grid algorithm, which relies on bounds. In this case, local non-smoothness is captured in terms of local bounds and grid resolution. Scaling Series works well for beliefs with sharp transitions, but without many discontinuities. GRAB is most appropriate for beliefs with many discontinuities. Both of these algorithms far outperform the prior art in terms of reliability, efficiency, and accuracy. GRAB is also able to guarantee that a quality approximation of the belief is produced. The proposed algorithms are evaluated on a diverse set of real robotics problems: tactile perception, autonomous driving, and mobile manipulation. In tactile perception, we localize objects in 3D starting with very high initial uncertainty and estimating all 6 degrees of freedom. The localization is performed based on tactile sensory data. Using Scaling Series, we obtain highly accurate and reliable results in under 1 second. Improved tactile object localization contributes to manufacturing applications, where tactile perception is widely used for workpiece localization. It also enables robotic applications in situations where vision can be obstructed, such as rescue robotics and underwater robotics. In autonomous driving, we detect and track vehicles in the vicinity of the robot based on 2D and 3D laser range finders. In addition to estimating position and velocity of vehicles, we also model and estimate their geometric shape. The geometric model leads to highly accurate estimates of pose and velocity for each vehicle. It also greatly simplifies association of data, which are often split up into separate clusters due to occlusion. The proposed Scaling Series algorithm greatly improves reliability and ensures that the problem is solved within tight real time constraints of autonomous driving. In mobile manipulation, we achieve highly accurate robot localization based on commonly used 2D laser range finders using the GRAB algorithm. We show that the high accuracy allows robots to navigate in tight spaces and manipulate objects without having to sense them directly. We demonstrate our approach on the example of simultaneous building navigation, door handle manipulation, and door opening. We also propose hybrid environment models, which combine high resolution polygons for objects of interest with low resolution occupancy grid representations for the rest of the environment. High accuracy indoor localization contributes directly to home/office mobile robotics as well as to future robotics applications in construction, inspection, and maintenance of buildings. Based on the success of the proposed perceptual inference algorithms in the concrete robotics problems, it is our hope that this thesis will serve as a starting point for further development of highly reliable perceptual inference methods.
Author: Fernández-Madrigal, Juan-Antonio Publisher: IGI Global ISBN: 1466621052 Category : Technology & Engineering Languages : en Pages : 499
Book Description
As mobile robots become more common in general knowledge and practices, as opposed to simply in research labs, there is an increased need for the introduction and methods to Simultaneous Localization and Mapping (SLAM) and its techniques and concepts related to robotics. Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods investigates the complexities of the theory of probabilistic localization and mapping of mobile robots as well as providing the most current and concrete developments. This reference source aims to be useful for practitioners, graduate and postgraduate students, and active researchers alike.
Author: Anibal Ollero Publisher: Springer ISBN: 3319708333 Category : Technology & Engineering Languages : en Pages : 906
Book Description
These volumes of "Advances in Intelligent Systems and Computing" highlight papers presented at the "Third Iberian Robotics Conference (ROBOT 2017)". Held from 22 to 24 November 2017 in Seville, Spain, the conference is a part of a series of conferences co-organized by SEIDROB (Spanish Society for Research and Development in Robotics) and SPR (Portuguese Society for Robotics). The conference is focused on Robotics scientific and technological activities in the Iberian Peninsula, although open to research and delegates from other countries. Thus, it has more than 500 authors from 21 countries. The volumes present scientific advances but also robotic industrial applications, looking to promote new collaborations between industry and academia.
Author: Alonzo Kelly Publisher: Springer ISBN: 3642134084 Category : Technology & Engineering Languages : en Pages : 514
Book Description
Robotics is undergoing a major transformation in scope and dimension. From a largely dominant industrial focus, robotics is rapidly expanding into human en- ronments and vigorously engaged in its new challenges. Interacting with, assi- ing, serving, and exploring with humans, the emerging robots will increasingly touch people and their lives. Beyond its impact on physical robots, the body of knowledge robotics has p- duced is revealing a much wider range of applications reaching across diverse research areas and scientific disciplines, such as: biomechanics, haptics, neuros- ences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the field of robotics. It is indeed at the int- section of disciplines that the most striking advances happen. The Springer Tracts in Advanced Robotics (STAR) is devoted to bringing to the research community the latest advances in the robotics field on the basis of their significance and quality. Through a wide and timely dissemination of critical - search developments in robotics, our objective with this series is to promote more exchanges and collaborations among the researchers in the community and c- tribute to further advancements in this rapidly growing field.
Author: Simon Rohou
Author: Simon Rohou
Author: Hanafiah Yussof
Author: David Israel González Aguirre
Author: Jose A. Castellanos
Author: Ansgar Bredenfeld
Author: Anna V. Petrovskaya
Author: Emanuele Frontoni
Author: Fernández-Madrigal, Juan-Antonio
Author: Anibal Ollero
Author: Alonzo Kelly