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FastSLAM - A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics (Hardcover, 2007 ed.): Michael... FastSLAM - A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics (Hardcover, 2007 ed.)
Michael Montemerlo, Sebastian Thrun
R3,241 R2,589 Discovery Miles 25 890 Save R652 (20%) Ships in 10 - 15 working days

This monograph describes a new family of algorithms for the simultaneous localization and mapping (SLAM) problem in robotics, called FastSLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy, in a number of robot application domains and have been successfully applied in different dynamic environments, including a solution to the problem of people tracking.

Principles of Robot Motion - Theory, Algorithms, and Implementations (Hardcover): Howie Choset, Kevin M. Lynch, Seth... Principles of Robot Motion - Theory, Algorithms, and Implementations (Hardcover)
Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, …
R1,771 Discovery Miles 17 710 Ships in 10 - 15 working days

A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.

Field and Service Robotics - Recent Advances in Research and Applications (Paperback, 2006 ed.): Shin'ichi Yuta, Hajime... Field and Service Robotics - Recent Advances in Research and Applications (Paperback, 2006 ed.)
Shin'ichi Yuta, Hajime Asama, Sebastian Thrun, Erwin Prassler, Takashi Tsubouchi
R7,278 Discovery Miles 72 780 Ships in 7 - 11 working days

This unique collection is the post-conference proceedings of the 4th "International Conference on Field and Service Robotics" (FSR). This book has authoritative contributors and presents current developments and new directions in field and service robotics. The book represents a cross-section of the current state of robotics research from one particular aspect: field and service applications, and how they reflect on the theoretical basis of subsequent developments.

Probabilistic Robotics (Hardcover): Sebastian Thrun, Wolfram Burgard, Dieter Fox Probabilistic Robotics (Hardcover)
Sebastian Thrun, Wolfram Burgard, Dieter Fox
R1,953 R1,653 Discovery Miles 16 530 Save R300 (15%) Ships in 10 - 15 working days

An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

Recent Advances in Robot Learning - Machine Learning (Paperback, Softcover reprint of the original 1st ed. 1996): Judy A.... Recent Advances in Robot Learning - Machine Learning (Paperback, Softcover reprint of the original 1st ed. 1996)
Judy A. Franklin, Tom M. Mitchell, Sebastian Thrun
R4,963 Discovery Miles 49 630 Ships in 7 - 11 working days

Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).

Robotics Research - Results of the 12th International Symposium ISRR (Paperback, Softcover reprint of hardcover 1st ed. 2007):... Robotics Research - Results of the 12th International Symposium ISRR (Paperback, Softcover reprint of hardcover 1st ed. 2007)
Sebastian Thrun, Rodney A Brooks, Hugh Durrant-Whyte
R6,871 Discovery Miles 68 710 Ships in 7 - 11 working days

This volume contains 50 papers presented at the 12th International Symposium of Robotics Research, which took place October 2005 in San Francisco, CA. Coverage includes: physical human-robot interaction, humanoids, mechanisms and design, simultaneous localization and mapping, field robots, robotic vision, robot design and control, underwater robotics, learning and adaptive behavior, networked robotics, and interfaces and interaction.

Robotics Research - Results of the 12th International Symposium ISRR (Hardcover, 2007 ed.): Sebastian Thrun, Rodney A Brooks,... Robotics Research - Results of the 12th International Symposium ISRR (Hardcover, 2007 ed.)
Sebastian Thrun, Rodney A Brooks, Hugh Durrant-Whyte
R7,788 R6,173 Discovery Miles 61 730 Save R1,615 (21%) Ships in 10 - 15 working days

This volume contains 50 papers presented at the 12th International Symposium of Robotics Research, which took place October 2005 in San Francisco, CA. Coverage includes: physical human-robot interaction, humanoids, mechanisms and design, simultaneous localization and mapping, field robots, robotic vision, robot design and control, underwater robotics, learning and adaptive behavior, networked robotics, and interfaces and interaction.

Field and Service Robotics - Recent Advances in Research and Applications (Hardcover, 2006 ed.): Shin'ichi Yuta, Hajime... Field and Service Robotics - Recent Advances in Research and Applications (Hardcover, 2006 ed.)
Shin'ichi Yuta, Hajime Asama, Sebastian Thrun, Erwin Prassler, Takashi Tsubouchi
R7,290 Discovery Miles 72 900 Ships in 7 - 11 working days

Since its inception in 1996, FSR, the biannual "International Conference on Field and Service Robotics" has published archival volumes of high reference value. This unique collection is the post-conference proceedings of the 4th FSR in Lake Yamanaka, Japan at July 2003. This book edited by Shina (TM)ichi Yuta, Hajime Asama, Sebastian Thrun, Erwin Prassler and Takashi Tsubouchi is rich by topics and authoritative contributors and presents the current developments and new directions in field and service robotics. The contents of these contributions represent a cross-section of the current state of robotics research from one particular aspect: field and service applications, and how they reflect on the theoretical basis of subsequent developments. Pursuing technologies aimed at realizing skilful, smart, reliable, robust field and service robots is the big challenge running throughout this focused collection.

Learning to Learn (Hardcover, 1998 ed.): Sebastian Thrun, Lorien Pratt Learning to Learn (Hardcover, 1998 ed.)
Sebastian Thrun, Lorien Pratt
R4,257 Discovery Miles 42 570 Ships in 7 - 11 working days

Over the past three decades or so, research on machine learning and data mining has led to a wide variety of algorithms that learn general functions from experience. As machine learning is maturing, it has begun to make the successful transition from academic research to various practical applications. Generic techniques such as decision trees and artificial neural networks, for example, are now being used in various commercial and industrial applications. Learning to Learn is an exciting new research direction within machine learning. Similar to traditional machine-learning algorithms, the methods described in Learning to Learn induce general functions from experience. However, the book investigates algorithms that can change the way they generalize, i.e., practice the task of learning itself, and improve on it. To illustrate the utility of learning to learn, it is worthwhile comparing machine learning with human learning. Humans encounter a continual stream of learning tasks. They do not just learn concepts or motor skills, they also learn bias, i.e., they learn how to generalize. As a result, humans are often able to generalize correctly from extremely few examples - often just a single example suffices to teach us a new thing. A deeper understanding of computer programs that improve their ability to learn can have a large practical impact on the field of machine learning and beyond. In recent years, the field has made significant progress towards a theory of learning to learn along with practical new algorithms, some of which led to impressive results in real-world applications. Learning to Learn provides a survey of some of the most exciting new research approaches, written by leading researchers in the field. Its objective is to investigate the utility and feasibility of computer programs that can learn how to learn, both from a practical and a theoretical point of view.

Recent Advances in Robot Learning - Machine Learning (Hardcover, Reprinted from MACHINE LEARNING, 23:2-3, 1996): Judy A.... Recent Advances in Robot Learning - Machine Learning (Hardcover, Reprinted from MACHINE LEARNING, 23:2-3, 1996)
Judy A. Franklin, Tom M. Mitchell, Sebastian Thrun
R4,973 Discovery Miles 49 730 Ships in 7 - 11 working days

Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).

Explanation-Based Neural Network Learning - A Lifelong Learning Approach (Hardcover, 1996 ed.): Sebastian Thrun Explanation-Based Neural Network Learning - A Lifelong Learning Approach (Hardcover, 1996 ed.)
Sebastian Thrun
R5,035 Discovery Miles 50 350 Ships in 7 - 11 working days

Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.' From the Foreword by Tom M. Mitchell.

FastSLAM - A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics (Paperback, Softcover reprint of... FastSLAM - A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics (Paperback, Softcover reprint of hardcover 1st ed. 2007)
Michael Montemerlo, Sebastian Thrun
R2,922 Discovery Miles 29 220 Out of stock

This monograph describes a new family of algorithms for the simultaneous localization and mapping (SLAM) problem in robotics, called FastSLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy, in a number of robot application domains and have been successfully applied in different dynamic environments, including a solution to the problem of people tracking.

Robotics - Science and Systems I (Paperback): Sebastian Thrun, Gaurav S. Sukhatme, Stefan Schaal Robotics - Science and Systems I (Paperback)
Sebastian Thrun, Gaurav S. Sukhatme, Stefan Schaal
R255 Discovery Miles 2 550 Out of stock

Papers presented at the inaugural Robotics: Science and Systems conference held at MIT in 2005. The new Robotics: Science and Systems conference spans all areas of robotics, bringing together researchers working on the algorithmic and mathematical foundations of robotics, robotics applications, and analysis of robotics systems. This volume contains papers presented at the inaugural conference, held at MIT in June, 2005. Additional information can be found at http://roboticsconference.org, or by clicking on the link to the left.

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