Possibilistic Sonar Modeling and Localization for Mobile Robots
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Total Pages | : |
Release | : 1997 |
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Total Pages | : |
Release | : 1997 |
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Author | : John J. Leonard |
Publisher | : Springer Science & Business Media |
Total Pages | : 199 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 1461536529 |
This monograph is a revised version of the D.Phil. thesis of the first author, submitted in October 1990 to the University of Oxford. This work investigates the problem of mobile robot navigation using sonar. We view model-based navigation as a process of tracking naturally occurring environment features, which we refer to as "targets". Targets that have been predicted from the environment map are tracked to provide that are observed, but not predicted, vehicle position estimates. Targets represent unknown environment features or obstacles, and cause new tracks to be initiated, classified, and ultimately integrated into the map. Chapter 1 presents a brief definition of the problem and a discussion of the basic research issues involved. No attempt is made to survey ex haustively the mobile robot navigation literature-the reader is strongly encouraged to consult other sources. The recent collection edited by Cox and Wilfong [34] is an excellent starting point, as it contains many of the standard works of the field. Also, we assume familiarity with the Kalman filter. There are many well-known texts on the subject; our notation derives from Bar-Shalom and Fortmann [7]. Chapter 2 provides a detailed sonar sensor model. A good sensor model of our approach to navigation, and is used both for is a crucial component predicting expected observations and classifying unexpected observations.
Author | : Mohammad Molhim |
Publisher | : |
Total Pages | : |
Release | : 2002 |
Genre | : |
ISBN | : |
Author | : Michael Drumheller |
Publisher | : |
Total Pages | : 24 |
Release | : 1985 |
Genre | : Automated guided vehicle systems |
ISBN | : |
This paper describes a method by which range data from a sonar or other type of rangefinder can be used to determine the 2-dimensional position and orientation of a mobile robot inside a room. The plan of the room is modeled as a list of segments indicating the positions of walls. The method works by extracting straight segments from the range data and examining all hypotheses about pairings between the segments and walls in the model of the room. Inconsistent pairings are discarded efficiently by using local constraints based on distances between walls, angles between walls, and ranges between walls along their normal vectors. These constraints are used to obtain a small set of possible positions, which is further pruned using a test for physical consistency. The approach is extremely tolerant of noise and clutter. Transient objects such as furniture and people need not be included in the room model, and very noisy, low-resolution sensors can be used. The algorithm's performance is demonstrated using a Polaroid Ultrasonic Rangefinder, which is a low-resolution, high-noise sensor.
Author | : Fernández-Madrigal, Juan-Antonio |
Publisher | : IGI Global |
Total Pages | : 497 |
Release | : 2012-09-30 |
Genre | : Technology & Engineering |
ISBN | : 1466621052 |
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 | : Taner Bilgic |
Publisher | : Springer |
Total Pages | : 751 |
Release | : 2003-08-03 |
Genre | : Technology & Engineering |
ISBN | : 3540449671 |
The refereed proceedings of the 10th International Fuzzy Systems Association World Congress, IFSA 2003, held in June/July 2003 in Istanbul, Turkey. The 84 papers presented together with 5 invited papers were carefully reviewed and selected form 318 submissions. The papers address all current issues in the area and present the state of the art in fuzzy sets, fuzzy systems, and fuzzy logic and their applications in a broad variety of fields. The papers are divided in four parts on mathematical issues, methodological issues, application areas, and cross-disciplinary issues.
Author | : Jonathan Scott Glennon |
Publisher | : |
Total Pages | : 109 |
Release | : 1998-06-01 |
Genre | : Autonomous robots |
ISBN | : 9781423559610 |
As we approach the new millennium, robots are playing an increasingly important role in our everyday lives. Robotics has evolved in industrial and military applications, and unmanned space exploration promises the continued development of ever-more-complex robots. Over the past few decades, research has focused on the development of autonomous mobile robots - robots that can move about without human supervision. This brings with it several problems, however, specifically the problem of localization. How can the robot determine its own position and orientation relative to the environment around it? Various methods of localization in mobile robots have been explored. Most of these methods, however, assume some a priori knowledge of the environment, or that the robot will have access to navigation beacons or Global Positioning Satellites. In this thesis, the foundations for feature-based localization are explored. An algorithm involving the Rough transform of range data and a neural network is developed, which enables the robot to find an unspecified number of wall-like features in its vicinity and determine the range and orientation of these walls relative to itself. Computation times are shown to be quite reasonable, and the algorithm is applied in both simulated and real-world indoor environments.
Author | : Khine Latt |
Publisher | : |
Total Pages | : 77 |
Release | : 1997-03-01 |
Genre | : |
ISBN | : 9781423572510 |
For an autonomous mobile robot to navigate in an unknown environment, it is essential to know the location of the robot on a real-time basis. Finding position and orientation of a mobile robot in a world coordinate system is a problem in localization. Dead-reckoning is commonly used for localization, but position and orientation errors from dead-reckoning tend to accumulate over time. The objective of this thesis is to develop a feature-based localization method that allows a mobile robot to re-calibrate its position and orientation by automatically selecting wall-like features in the environment. In this thesis, the selection of features is accomplished by applying the Hough transform to sonar data. The Hough transform makes it possible to select the optimal feature (the longest wall, in this case) without finding all possible line segments from the sonar data. A least-square line fitting method is then employed to construct a model of the line segment that represents the feature selected by the Hough transform. The algorithm developed was tested using synthetic and real sonar data. Experimental results demonstrated the effectiveness of the proposed localization methods.
Author | : Simon Rohou |
Publisher | : John Wiley & Sons |
Total Pages | : 293 |
Release | : 2020-01-02 |
Genre | : Technology & Engineering |
ISBN | : 1848219709 |
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 | : Antoni Burguera |
Publisher | : |
Total Pages | : |
Release | : 2009 |
Genre | : Technology |
ISBN | : |
Mobile Robot Localization using Particle Filters and Sonar Sensors.