Principles of Robot Motion

Author: Howie M. Choset
Publisher: MIT Press
ISBN: 9780262033275
Format: PDF
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A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts.

Probabilistic Robotics

Author: Sebastian Thrun
Publisher: MIT Press
ISBN: 0262201623
Format: PDF, Mobi
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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
Publisher: MIT Press
ISBN: 0262015358
Format: PDF, ePub, Mobi
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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.

Autonomous Robots

Author: George A. Bekey
Publisher: MIT Press
ISBN: 9780262025782
Format: PDF, Mobi
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An introduction to the science and practice of autonomous robots that reviews over 300 current systems and examines the underlying technology.

Behavior based Robotics

Author: Ronald C. Arkin
Publisher: MIT Press
ISBN: 9780262011655
Format: PDF, Kindle
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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.

Mechanics of Robotic Manipulation

Author:
Publisher: MIT Press
ISBN: 9780262263740
Format: PDF, Kindle
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"Manipulation" refers to a variety of physical changes made to the world around us. Mechanics of Robotic Manipulation addresses one form of robotic manipulation, moving objects, and the various processes involved -- grasping, carrying, pushing, dropping, throwing, and so on. Unlike most books on the subject, it focuses on manipulation rather than manipulators. This attention to processes rather than devices allows a more fundamental approach, leading to results that apply to a broad range of devices, not just robotic arms.The book draws both on classical mechanics and on classical planning, which introduces the element of imperfect information. The book does not propose a specific solution to the problem of manipulation, but rather outlines a path of inquiry.

Planning Algorithms

Author: Steven M. LaValle
Publisher: Cambridge University Press
ISBN: 1139455176
Format: PDF, Docs
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Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning, but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the 'configuration spaces' of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. This text and reference is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Mobile Robotics

Author: Alonzo Kelly
Publisher: Cambridge University Press
ISBN: 110703115X
Format: PDF, ePub, Mobi
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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.

Modern Robotics

Author: Kevin M. Lynch
Publisher: Cambridge University Press
ISBN: 1107156300
Format: PDF, Docs
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A modern and unified treatment of the mechanics, planning, and control of robots, suitable for a first course in robotics.

Introduction to AI Robotics

Author: Robin Murphy
Publisher: MIT Press
ISBN: 9780262133838
Format: PDF, Mobi
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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.