probabilistic robotics intelligent robotics and autonomous agents series

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Probabilistic Robotics

Author : Sebastian Thrun
ISBN : 9780262303804
Genre : Technology & Engineering
File Size : 52. 58 MB
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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.

Probabilistic Robotics

Author : Sebastian Thrun
ISBN : 9780262201629
Genre : Technology & Engineering
File Size : 57. 88 MB
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Probablistic robotics is a growing area in the subject, concerned with perception and control in the face of uncertainty and giving robots a level of robustness in real-world situations. This book introduces techniques and algorithms in the field.

Introduction To Autonomous Mobile Robots

Author : Roland Siegwart
ISBN : 9780262015356
Genre : Computers
File Size : 49. 62 MB
Format : PDF
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Machine generated contents note: |g 1. |t Introduction -- |g 1.1. |t Introduction -- |g 1.2. |t An Overview of the Book -- |g 2. |t Locomotion -- |g 2.1. |t Introduction -- |g 2.1.1. |t Key issues for locomotion -- |g 2.2. |t Legged Mobile Robots -- |g 2.2.1. |t Leg configurations and stability -- |g 2.2.2. |t Consideration of dynamics -- |g 2.2.3. |t Examples of legged robot locomotion -- |g 2.3. |t Wheeled Mobile Robots -- |g 2.3.1. |t Wheeled locomotion: The design space -- |g 2.3.2. |t Wheeled locomotion: Case studies -- |g 2.4. |t Aerial Mobile Robots -- |g 2.4.1. |t Introduction -- |g 2.4.2. |t Aircraft configurations -- |g 2.4.3. |t State of the art in autonomous VTOL -- |g 2.5. |t Problems -- |g 3. |t Mobile Robot Kinematics -- |g 3.1. |t Introduction -- |g 3.2. |t Kinematic Models and Constraints -- |g 3.2.1. |t Representing robot position -- |g 3.2.2. |t Forward kinematic models -- |g 3.2.3. |t Wheel kinematic constraints -- |g 3.2.4. |t Robot kinematic constraints -- |g 3.g 3.3. |t Mobile Robot Maneuverability -- |g 3.3.1. |t Degree of mobility -- |g 3.3.2. |t Degree of steerability -- |g 3.3.3. |t Robot maneuverability -- |g 3.4. |t Mobile Robot Workspace -- |g 3.4.1. |t Degrees of freedom -- |g 3.4.2. |t Holonomic robots -- |g 3.4.3. |t Path and trajectory considerations -- |g 3.5. |t Beyond Basic Kinematics -- |g 3.6. |t Motion Control (Kinematic Control) -- |g 3.6.1. |t Open loop control (trajectory-following) -- |g 3.6.2. |t Feedback control -- |g 3.7. |t Problems -- |g 4. |t Perception -- |g 4.1. |t Sensors for Mobile Robots -- |g 4.1.1. |t Sensor classification -- |g 4.1.2. |t Characterizing sensor performance -- |g 4.1.3. |t Representing uncertainty -- |g 4.1.4. |t Wheel/motor sensors -- |g 4.1.5. |t Heading sensors -- |g 4.1.6. |t Accelerometers -- |g 4.1.7. |t Inertial measurement unit (IMU) -- |g 4.1.8. |t Ground beacons -- |g 4.1.9. |t Active ranging -- |g 4.1.10. |t Motion/speed sensors -- |g 4.1.11. |t Vision sensors -- |g 4.2. |t Fundameng 4.2.5. |t Structure from stereo -- |g 4.2.6. |t Structure from motion -- |g 4.2.7. |t Motion and optical flow -- |g 4.2.8. |t Color tracking -- |g 4.3. |t Fundamentals of Image Processing -- |g 4.3.1. |t Image filtering -- |g 4.3.2. |t Edge detection -- |g 4.3.3. |t Computing image similarity -- |g 4.4. |t Feature Extraction -- |g 4.5. |t Image Feature Extraction: Interest Point Detectors -- |g 4.5.1. |t Introduction -- |g 4.5.2. |t Properties of the ideal feature detector -- |g 4.5.3. |t Corner detectors -- |g 4.5.4. |t Invariance to photometric and geometric changes -- |g 4.5.5. |t Blob detectors -- |g 4.6. |t Place Recognition -- |g 4.6.1. |t Introduction -- |g 4.6.2. |t From bag of features to visual words -- |g 4.6.3. |t Efficient location recognition by using an inverted file -- |g 4.6.4. |t Geometric verification for robust place recognition -- |g 4.6.5. |t Applications -- |g 4.6.6. |t Other image representations for place recognition -- |g 4.7. |t Feature Extraction Based ong 4.7.3. |t Range histogram features -- |g 4.7.4. |t Extracting other geometric features -- |g 4.8. |t Problems -- |g 5. |t Mobile Robot Localization -- |g 5.1. |t Introduction -- |g 5.2. |t The Challenge of Localization: Noise and Aliasing -- |g 5.2.1. |t Sensor noise -- |g 5.2.2. |t Sensor aliasing -- |g 5.2.3. |t Effector noise -- |g 5.2.4. |t An error model for odometric position estimation -- |g 5.3. |t To Localize or Not to Localize: Localization-Based Navigation Versus Programmed Solutions -- |g 5.4. |t Belief Representation -- |g 5.4.1. |t Single-hypothesis belief -- |g 5.4.2. |t Multiple-hypothesis belief -- |g 5.5. |t Map Representation -- |g 5.5.1. |t Continuous representations -- |g 5.5.2. |t Decomposition strategies -- |g 5.5.3. |t State of the art: Current challenges in map representation -- |g 5.6. |t Probabilistic Map-Based Localization -- |g 5.6.1. |t Introduction -- |g 5.6.2. |t The robot localization problem -- |g 5.6.3. |t Basic concepts of probability theory -- |gg 5.6.6. |t Classification of localization problems -- |g 5.6.7. |t Markov localization -- |g 5.6.8. |t Kalman filter localization -- |g 5.7. |t Other Examples of Localization Systems -- |g 5.7.1. |t Landmark-based navigation -- |g 5.7.2. |t Globally unique localization -- |g 5.7.3. |t Positioning beacon systems -- |g 5.7.4. |t Route-based localization -- |g 5.8. |t Autonomous Map Building -- |g 5.8.1. |t Introduction -- |g 5.8.2. |t SLAM: The simultaneous localization and mapping problem -- |g 5.8.3. |t Mathematical definition of SLAM -- |g 5.8.4. |t Extended Kalman Filter (EKF) SLAM -- |g 5.8.5. |t Visual SLAM with a single camera -- |g 5.8.6. |t Discussion on EKF SLAM -- |g 5.8.7. |t Graph-based SLAM -- |g 5.8.8. |t Particle filter SLAM -- |g 5.8.9. |t Open challenges in SLAM -- |g 5.8.10. |t Open source SLAM software and other resources -- |g 5.9. |t Problems -- |g 6. |t Planning and Navigation -- |g 6.1. |t Introduction -- |g 6.2. |t Competences for Navigation: Planning and Reactig 6.4. |t Obstacle avoidance -- |g 6.4.1. |t Bug algorithm -- |g 6.4.2. |t Vector field histogram -- |g 6.4.3. |t The bubble band technique -- |g 6.4.4. |t Curvature velocity techniques -- |g 6.4.5. |t Dynamic window approaches -- |g 6.4.6. |t The Schlegel approach to obstacle avoidance -- |g 6.4.7. |t Nearness diagram -- |g 6.4.8. |t Gradient method -- |g 6.4.9. |t Adding dynamic constraints -- |g 6.4.10. |t Other approaches -- |g 6.4.11. |t Overview -- |g 6.5. |t Navigation Architectures -- |g 6.5.1. |t Modularity for code reuse and sharing -- |g 6.5.2. |t Control localization -- |g 6.5.3. |t Techniques for decomposition -- |g 6.5.4. |t Case studies: tiered robot architectures -- |g 6.6. |t Problems -- |t Bibliography -- |t Books -- |t Papers -- |t Referenced Webpages.

Introduction To Ai Robotics

Author : Robin Murphy
ISBN : 0262133830
Genre : Computers
File Size : 79. 87 MB
Format : PDF
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A comprehensive introduction to the AI approach to robotics, combining theoretical rigor and practical applications; with case studies and exercises. This text covers all the material needed to understand the principles behind the AI approach to robotics and to program an artificially intelligent robot for applications involving sensing, navigation, planning, and uncertainty. Robin Murphy is extremely effective at combining theoretical and practical rigor with a light narrative touch. In the overview, for example, she touches upon anthropomorphic robots from classic films and science fiction stories before delving into the nuts and bolts of organizing intelligence in robots. Following the overview, Murphy contrasts AI and engineering approaches and discusses what she calls the three paradigms of AI robotics: hierarchical, reactive, and hybrid deliberative/reactive. Later chapters explore multiagent scenarios, navigation and path-planning for mobile robots, and the basics of computer vision and range sensing. Each chapter includes objectives, review questions, and exercises. Many chapters contain one or more case studies showing how the concepts were implemented on real robots. Murphy, who is well known for her classroom teaching, conveys the intellectual adventure of mastering complex theoretical and technical material. An Instructor's Manual including slides, solutions, sample tests, and programming assignments is available to qualified professors who are considering using the book or who are using the book for class use.

The Robotics Primer

Author : Maja J. Matarić
ISBN : 9780262633543
Genre : Computers
File Size : 26. 69 MB
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1. What is a robot? 2. Where do robots come from? 3. What's in a robot? 4. Arms, legs, wheels, tracks, and really drives them 5. Move it! 6. Grasping at straws 7. What's going on? 8. Switch on ghe light 9. Sonars, lasers, and cameras 10. Stay in control 11. The building bolcks of control 12. What's in your head? 13. Think hard, act later 14. Don't think, react! 15. Think and act separately, in parallel 16. Think the way you act 17. Making your robot behave 18. When the unexpected happens 19. Going places 20. Go, team! 21. Things keep getting better 22. Where to next?

Probabilistic Approaches To Robotic Perception

Author : João Filipe Ferreira
ISBN : 9783319020068
Genre : Technology & Engineering
File Size : 44. 40 MB
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This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot? How should a robotic system perceive, infer, decide and act efficiently? These are two of the challenging questions robotics community and robotic researchers have been facing. The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public’s imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited. In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the “irreducible incompleteness of models”.

Mobile Robotics

Author : Alonzo Kelly
ISBN : 9781107031159
Genre : Computers
File Size : 73. 56 MB
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Mobile Robotics offers comprehensive coverage of the essentials of the field suitable for both students and practitioners. Adapted from Alonzo Kelly's graduate and undergraduate courses, the content of the book reflects current approaches to developing effective mobile robots. Professor Kelly adapts principles and techniques from the fields of mathematics, physics, and numerical methods to present a consistent framework in a notation that facilitates learning and highlights relationships between topics. This text was developed specifically to be accessible to senior level undergraduates in engineering and computer science, and includes supporting exercises to reinforce the lessons of each section. Practitioners will value Kelly's perspectives on practical applications of these principles. Complex subjects are reduced to implementable algorithms extracted from real systems wherever possible, to enhance the real-world relevance of the text.

3d Robotic Mapping

Author : Andreas Nüchter
ISBN : 9783540898832
Genre : Technology & Engineering
File Size : 40. 22 MB
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Focuses on acquiring spatial models of physical environments through mobile robots The robotic mapping problem is commonly referred to as SLAM (simultaneous localization and mapping). 3D maps are necessary to avoid collisions with complex obstacles and to self-localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle) New solutions to the 6D SLAM problem for 3D laser scans are proposed and a wide variety of applications are presented

Behavior Based Robotics

Author : Ronald C. Arkin
ISBN : 0262011654
Genre : Computers
File Size : 58. 27 MB
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foreword by Michael Arbib "Hard to put down and necessary to know -- Arkin's book provides a comprehensive intellectual history of robots and a thorough compilation of robotic organizational paradigms from reflexes through social interaction." -- Chris Brown, Professor of Computer Science, University of Rochester This introduction to the principles, design, and practice of intelligent behavior-based autonomous robotic systems is the first true survey of this robotics field. The author presents the tools and techniques central to the development of this class of systems in a clear and thorough manner. Following a discussion of the relevant biological and psychological models of behavior, he covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence. The text throughout refers to actual implemented robots and includes many pictures and descriptions of hardware, making it clear that these are not abstract simulations, but real machines capable of perception, cognition, and action.

Simultaneous Localization And Mapping For Mobile Robots Introduction And Methods

Author : Fernández-Madrigal, Juan-Antonio
ISBN : 9781466621053
Genre : Technology & Engineering
File Size : 58. 34 MB
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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.

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