What is the main focus of the book 'Probabilistic Robotics'?

The book 'Probabilistic Robotics' primarily focuses on the application of probabilistic methods in the field of robotics. It covers essential algorithms used in perception, localization, and decision-making processes in autonomous agents. This comprehensive approach enables readers to understand how robots interact with uncertain environments, making it highly relevant for those studying artificial intelligence and robotics.

Who are the authors of 'Probabilistic Robotics' and why are they significant?

'Probabilistic Robotics' is authored by Sebastian Thrun, Wolfram Burgard, and Dieter Fox, who are renowned experts in the fields of robotics and artificial intelligence. Their combined expertise and contributions to the field make this book a crucial resource for both scholars and practitioners. The authors emphasize practical applications of theoretical concepts, ensuring readers can implement learned methods in real-world scenarios.

Can beginners in robotics understand the content of this book?

Yes, while 'Probabilistic Robotics' is a technical book, it caters to a range of audiences, including beginners. The authors introduce core concepts methodically, with clear explanations and illustrative examples. Although a basic understanding of probability and current robotics principles is beneficial, the book encourages readers to grow their knowledge progressively, making it suitable for self-study and academic courses alike.

What are some key topics covered in 'Probabilistic Robotics'?

Key topics in 'Probabilistic Robotics' include mapping and localization, sensor models, filtering techniques, and the use of Bayesian networks. These concepts are essential for developing robust robotic systems capable of navigating and interpreting dynamic environments. By addressing various algorithms and their implementations, the book equips readers with the foundational tools to tackle real-life robotic challenges.

Is 'Probabilistic Robotics' suitable for academic use?

Absolutely! 'Probabilistic Robotics' is widely used in academic settings, particularly in courses focused on robotics, artificial intelligence, and related engineering fields. Its thorough examination of probabilistic approaches allows educators to integrate theoretical knowledge with practical applications. Furthermore, the book's exercises and case studies encourage critical thinking and problem-solving among students, reinforcing their learning experiences.

How does this book contribute to advancements in autonomous robotics?

'Probabilistic Robotics' contributes significantly to advancements in autonomous robotics by introducing robust algorithms that enhance decision-making in unpredictable environments. The concepts outlined in the book help developers create smarter robotic systems that can think independently and adapt to unforeseen challenges. As industries increasingly implement automated solutions, the insights gained from this book continue to drive innovation and efficiency.

What makes this book different from other robotics literature?

'Probabilistic Robotics' stands out due to its comprehensive focus on the probabilistic framework for robotic systems. While many robotics books may cover basic principles or specific technologies, this book uniquely integrates theoretical concepts with practical algorithms across various applications. Its accessibility and depth make it a go-to resource for anyone looking to deeply understand robotics in uncertain environments.

Can I find practical examples or case studies in 'Probabilistic Robotics'?

Yes, 'Probabilistic Robotics' includes numerous practical examples and case studies that illustrate the application of concepts covered in the book. These real-world scenarios provide insights into how probabilistic methods are deployed in actual robotic systems, facilitating a better understanding of theoretical principles in practice. These examples are beneficial for readers looking to apply learned knowledge to real-life projects.

What prior knowledge is helpful before reading this book?

Before diving into 'Probabilistic Robotics,' having prior knowledge in basic probability theory, linear algebra, and general robotics principles can be beneficial. Familiarity with programming languages, particularly those related to automation and robotics, will also enhance your ability to grasp the techniques presented in the book. This foundational knowledge will facilitate a more comprehensive understanding of the advanced topics discussed.

Where can I buy 'Probabilistic Robotics' in Liechtenstein?

You can purchase 'Probabilistic Robotics' at Ubuy, which is a reliable online shopping platform that offers a diverse range of books, including the Intelligent Robotics and Autonomous Agents series. Ubuy provides convenient shipping options to Liechtenstein, ensuring that you can easily access this essential resource for your studies or professional development in robotics.

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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

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Artikelnr.: 19747895

Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

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Artikelnr.: 19747895

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Comprehensive Coverage

This book offers in-depth coverage of probabilistic methods in robotics, making it an essential resource for researchers and practitioners seeking to implement advanced algorithms in autonomous systems.

Foundational Concepts

It introduces foundational concepts in robotics and probability, equipping readers with the necessary knowledge to understand and apply complex robotics techniques effectively in real-world scenarios.

Expert Insights

Authored by leaders in the field, this text provides unique insights and practical examples, ensuring that readers gain valuable perspectives that enhance their expertise in intelligent robotics.

Produktdetails

Introduces techniques and algorithms in the field of probabilistic robotics
Focuses on perception and control in uncertain environments
Based on mathematical statistics, providing robots with robustness in real-world situations
Includes example implementations, mathematical derivations, and extensive exercises
Relevant for robotic software development, scientific research, and applied statisticians
Offers additional material on the book's website

Publisher	The MIT Press
Publication date	August 19, 2005
Edition	Intelligent Robotics and Autonomous Agents series
Language	English
Print length	672 pages
ISBN-10	0262201623
ISBN-13	978-0262201629
Item Weight	2.93 pounds (1.33 kg)
Dimensions	8.31 x 1.54 x 9.25 inches (21.1 x 3.9 x 23.5 cm)

Für wen ist das Produkt geeignet?

University Students
Ideal for advanced students studying robotics, artificial intelligence, or control systems seeking a deep understanding of probabilistic methods.
Research Professionals
Researchers and practitioners in robotics or automation will benefit from the comprehensive methodologies and algorithms presented in this book.
Engineers in Robotics
Engineers working on autonomous systems will find practical applications and insights to enhance their designs and implementations.

Casual Readers
Individuals without a technical background may find the mathematical concepts and theories too challenging to understand.

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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

About This Item

Experience the fascinating world of robotics with Probabilistic Robotics, part of the Intelligent Robotics and Autonomous Agents series. This comprehensive hardcover book, written by Sebastian Thrun, Wolfram Burgard, and Dieter Fox, delves into the core concepts and advanced methods of estimation theory, as well as the probabilistic models and processes that drive robot localization, SLAM (Simultaneous Localization and Mapping), and decision making. Whether you are a student, teacher, or researcher, Probabilistic Robotics is an essential reference that will expand your understanding of robotics. With its in-depth coverage and practical insights, this book is a must-have textbook that will equip you with the tools and knowledge needed to navigate the complex realm of uncertainty in robotics. Discover the techniques, concepts, and applications of Probabilistic Robotics as you embark on an intellectual journey through its pages.

From the basics to advanced topics, this book provides a comprehensive overview of the field, making it suitable for beginners and experienced practitioners alike. Written by esteemed authors who are experts in their respective fields, Probabilistic Robotics offers an authoritative perspective on the subject. Sebastian Thrun, Associate Professor at Stanford University and Director of the Stanford AI Lab, brings his wealth of knowledge and experience to the table. Wolfram Burgard, Professor at the University of Freiburg, and Dieter Fox, Associate Professor at the University of Washington, contribute their extensive research and expertise to the book. Whether you are interested in learning about the fundamental concepts of Probabilistic Robotics, exploring innovative research advancements, or understanding the practical applications of this field, this book has something for everyone.

Join the ranks of robotics enthusiasts and professionals and unlock the potential of Probabilistic Robotics today.

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Essential reference for students, teachers, and researchers
Covers basics and advanced methods of estimation theory
Discusses probabilistic models and processes in robot localization, SLAM, and decision-making
Replete with material for students and practitioners
Written by renowned authors in the field
Highly recommended resource

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Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

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