Wheeled mobile robotics : from fundamentals towards autonomous systems
(eBook)

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Oxford, United Kingdom : Butterworth-Heinemann, [2017].
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eBook
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0128042389, 9780128042380
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1 online resource (1 volume) : illustrations
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English

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Includes bibliographical references and index.
Description
Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems covers the main topics from the wide area of mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB® script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization. It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained. Offers comprehensive coverage of the essentials of the field that are suitable for both academics and practitioners Includes several examples of the application of algorithms in simulations and real laboratory projects Presents foundation in mobile robotics theory before continuing with more advanced topics Self-sufficient to beginner readers, covering all important topics in the mobile robotics field Contains specific topics on modeling, control, sensing, path planning, localization, design architectures, and multi-agent systems.

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APA Citation, 7th Edition (style guide)

Klančar, G., Zdešar, A., Blažič, S., & Škrjanc, I. (2017). Wheeled mobile robotics: from fundamentals towards autonomous systems . Butterworth-Heinemann.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Gregor, Klančar et al.. 2017. Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems. Butterworth-Heinemann.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Gregor, Klančar et al.. Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems Butterworth-Heinemann, 2017.

MLA Citation, 9th Edition (style guide)

Klančar, Gregor,, Andrej Zdešar, Sašo Blažič, and Igor Škrjanc. Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems Butterworth-Heinemann, 2017.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Full titlewheeled mobile robotics from fundamentals towards autonomous systems
Authorklančar gregor
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Last Update2024-09-06 16:31:08PM
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24510|a Wheeled mobile robotics :|b from fundamentals towards autonomous systems /|c Gregor Klancar, Andrej Zdesar, Saso Blazic, Igor Škrjanc.
264 1|a Oxford, United Kingdom :|b Butterworth-Heinemann,|c [2017]
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504 |a Includes bibliographical references and index.
5050 |a Front Cover -- Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems -- Copyright -- Contents -- Preface -- Acknowledgements -- Chapter 1: Introduction to Mobile Robotics -- 1.1 Introduction -- 1.1.1 Robots -- 1.1.2 Mobile -- 1.1.3 Wheels -- 1.1.4 Autonomous Mobile Systems -- 1.2 History -- 1.3 About the Book -- References -- Chapter 2: Motion Modeling for Mobile Robots -- 2.1 Introduction -- 2.2 Kinematics of Wheeled Mobile Robots -- 2.2.1 Differential Drive -- 2.2.2 Bicycle Drive -- 2.2.3 Tricycle Drive -- 2.2.4 Tricycle With a Trailer -- 2.2.5 Car (Ackermann) Drive -- 2.2.6 Synchronous Drive -- 2.2.7 Omnidirectional Drive -- 2.2.8 Tracked Drive -- 2.3 Motion Constraints -- 2.3.1 Holonomic Constraints -- 2.3.2 Nonholonomic Constraints -- 2.3.3 Integrability of Constraints -- 2.3.4 Vector Fields, Distribution, Lie Bracket -- 2.3.5 Controllability of Wheeled Mobile Robots -- 2.4 Dynamic Model of a Mobile System With Constraints -- 2.4.1 State-Space Representation of the Dynamic Model of a Mobile System With Constraints -- 2.4.2 Kinematic and Dynamic Model of Differential Drive Robot -- Kinematic Model and Constraints -- Dynamic Model -- References -- Chapter 3: Control of Wheeled Mobile Systems -- 3.1 Introduction -- 3.2 Control to Reference Pose -- 3.2.1 Orientation Control -- 3.2.2 Forward-Motion Control -- 3.2.3 Basic Approaches -- Control to Reference Position -- Control to Reference Pose Using an Intermediate Point -- Control to Reference Pose Using an Intermediate Direction -- Control on a Segmented Continuous Path Determined by a Line and a Circle Arc -- From Reference Pose Control to Reference Path Control -- 3.3 Trajectory Tracking Control -- 3.3.1 Trajectory Tracking Control Using Basic Approaches -- 3.3.2 Decomposing Control to Feedforward and Feedback Action -- 3.3.3 Feedback Linearization.
5058 |a 3.3.4 Development of the Kinematic Trajectory-Tracking Error Model -- 3.3.5 Linear Controller -- 3.3.6 Lyapunov-Based Control Design -- 3.3.7 Takagi-Sugeno Fuzzy Control Design in the LMI Framework -- Takagi-Sugeno Fuzzy Error Model of a Differentially Driven Wheeled Mobile Robot -- PDC Control of a Differentially Driven Wheeled Mobile Robot -- 3.3.8 Model-Based Predictive Control -- Discrete MPC -- 3.3.9 Particle Swarm Optimization-Based Control -- MPC With PSO -- 3.3.10 Visual Servoing Approaches for Solving the Control Problems in Mobile Robotics -- 3.4 Optimal Velocity Profile Estimation for a Known Path -- References -- Chapter 4: Path Planning -- 4.1 Introduction -- 4.1.1 Robot Environment -- 4.1.2 Path Planning -- 4.1.3 Configuration and Configuration Space -- 4.1.4 Mathematical Description of Obstacle Shape and Pose in the Environment -- Border-Based Description of Obstacles -- Obstacle Description Using Intersecting Half-Planes -- 4.2 Environment Presentation for Path Planning Purposes -- 4.2.1 Graph Representation -- 4.2.2 Cell Decomposition -- Accurate Decomposition to Cells -- Approximate Decomposition to Cells -- 4.2.3 Roadmap -- Visibility Graph -- Voronoi Graph -- Triangulation -- 4.2.4 Potential Field -- 4.2.5 Sampling-Based Path-Planning -- RRT Method -- PRM Method -- 4.3 Simple Path Planning Algorithms:Bug Algorithms -- 4.3.1 Bug0 Algorithm -- 4.3.2 Bug1 Algorithm -- 4.3.3 Bug2 Algorithm -- 4.4 Graph-Based Path Planning Methods -- 4.4.1 Breadth-First Search -- 4.4.2 Depth-First Search -- 4.4.3 Iterative Deepening Depth-First Search -- 4.4.4 Dijkstra's Algorithm -- 4.4.5 A∗ Algorithm -- 4.4.6 Greedy Best-First Search -- References -- Chapter 5: Sensors Used in Mobile Systems -- 5.1 Introduction -- 5.2 Coordinate Frame Transformations -- 5.2.1 Orientation and Rotation -- 5.2.2 Translation and Rotation.
5058 |a 5.2.3 Kinematics of Rotating Frames -- Rotational Kinematics Expressed by Quaternions -- 5.2.4 Projective Geometry -- Multiview Geometry -- Singular Cases -- 3D Reconstruction -- 5.3 Pose Measurement Methods -- 5.3.1 Dead Reckoning -- Odometry -- Inertial Navigation -- 5.3.2 Heading Measurement -- 5.3.3 Active Markers and Global Position Measurement -- Global Navigation Satellite System -- 5.3.4 Navigation Using Environmental Features -- Straight-Line Features -- Split-and-Merge Algorithm -- Evolving Straight-Line Clustering -- Hough Transform -- Color Features -- Artificial Pattern Markers -- Natural Local Image Features -- 5.3.5 Matching of Environment Models: Maps -- 5.4 Sensors -- 5.4.1 Sensor Characteristics -- 5.4.2 Sensor Classifications -- References -- Chapter 6: Nondeterministic Events in Mobile Systems -- 6.1 Introduction -- 6.2 Basics of Probability -- 6.2.1 Discrete Random Variable -- 6.2.2 Continuous Random Variable -- 6.2.3 Bayes' Rule -- 6.3 State Estimation -- 6.3.1 Disturbances and Noise -- 6.3.2 Estimate Convergence and Bias -- 6.3.3 Observability -- 6.4 Bayesian Filter -- 6.4.1 Markov Chains -- 6.4.2 State Estimation From Observations -- 6.4.3 State Estimation From Observations and Actions -- 6.4.4 Localization Example -- 6.4.5 Environment Sensing -- 6.4.6 Motion in the Environment -- 6.4.7 Localization in the Environment -- 6.5 Kalman Filter -- 6.5.1 Kalman Filter in Matrix Form -- 6.5.2 Extended Kalman Filter -- 6.5.3 Kalman Filter Derivatives -- 6.6 Particle Filter -- References -- Chapter 7: Autonomous Guided Vehicles -- 7.1 Introduction -- 7.2 Autonomous Transportation Vehicles -- 7.2.1 About -- 7.2.2 Setup -- 7.2.3 Sensors -- 7.2.4 Localization and Mapping -- 7.2.5 Control -- 7.2.6 Path Planning -- 7.2.7 Decision Making -- 7.3 Wheeled Mobile Robots in Agriculture -- 7.3.1 Introduction (About) -- 7.3.2 Service Unit Setup.
5058 |a 7.3.3 Localization, Mapping, and SLAM -- 7.3.4 Control Strategies -- 7.3.5 Planning Routes and Scheduling -- 7.4 Wheeled Mobile Robots in Industry -- 7.4.1 About -- 7.4.2 Setup -- 7.4.3 Sensors -- 7.4.4 Localization and Mapping -- 7.4.5 Control -- 7.4.6 Path Planning -- 7.4.7 Decision Making -- 7.5 Wheeled Mobile Robots in Domestic Environments -- 7.5.1 About -- 7.5.2 Setup -- 7.5.3 Sensors -- 7.5.4 Localization and Mapping -- 7.5.5 Path Planning -- 7.5.6 Control -- 7.5.7 Decision Making -- 7.6 Assistive Mobile Robots in Walking Rehabilitation Therapy -- 7.6.1 About -- 7.6.2 Setup -- 7.6.3 Sensors -- 7.6.4 Localization and Mapping -- 7.6.5 Control -- 7.6.6 Path Planning -- References -- Chapter 8: Project Examples for Laboratory Practice -- 8.1 Introduction -- 8.2 Localization Based on Bayesian Filter Within a Network of Paths and Crossroads -- 8.2.1 Introduction -- 8.2.2 Line Following -- 8.2.3 Odometry -- 8.2.4 Map Building -- 8.2.5 Localization -- 8.3 Localization Based on Extended Kalman Filter Using Indoor Global Positioning System and Odometry -- 8.3.1 Introduction -- 8.3.2 Experimental Setup -- 8.3.3 Extended Kalman Filter -- 8.4 Particle-Filter-Based Localization in a Pattern of Colored Tiles -- 8.4.1 Introduction -- 8.4.2 Experimental Setup -- 8.4.3 Manual Control -- 8.4.4 Wheel Odometry -- 8.4.5 Color Sensor Calibration -- 8.4.6 Particle Filter -- 8.5 Control of Vehicles in a Linear Formation -- 8.5.1 Introduction -- 8.5.2 Localization Using Odometry -- 8.5.3 Estimating Reference Trajectory -- 8.5.4 Linear Formation Control -- 8.6 Motion and Strategy Control of Multiagent Soccer Robots -- 8.6.1 Introduction -- 8.6.2 Motion Control -- 8.6.3 Behavior-Based Agent Operation -- 8.6.4 Multiagent Game Strategy -- 8.7 Image-Based Control of a Mobile Robot -- 8.7.1 Introduction -- 8.7.2 Experimental Setup -- 8.7.3 Position-Based Visual Servoing.
5058 |a 8.7.4 Image-Based Visual Servoing -- 8.7.5 Natural Image Features -- 8.8 Particle-Filter-Based Localization Using an Array of Ultrasonic Distance Sensors -- 8.8.1 Introduction -- 8.8.2 Predicting Particles' Locations From Known Robot Motion -- 8.8.3 Sensor Model for Particle Measurement Prediction -- 8.8.4 Correction Step of Particle Filter and Robot Pose Estimate -- 8.9 Path Planning of a Mobile Robot in a Known Environment -- 8.9.1 Experimental Setup -- 8.9.2 A* Path Searching Algorithm -- 8.9.3 Optimum Path in the Map of the Environment -- References -- Index -- Back Cover.
520 |a Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems covers the main topics from the wide area of mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB® script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization. It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained. Offers comprehensive coverage of the essentials of the field that are suitable for both academics and practitioners Includes several examples of the application of algorithms in simulations and real laboratory projects Presents foundation in mobile robotics theory before continuing with more advanced topics Self-sufficient to beginner readers, covering all important topics in the mobile robotics field Contains specific topics on modeling, control, sensing, path planning, localization, design architectures, and multi-agent systems.
5880 |a Online resource; title from title page (Safari, viewed March 10, 2017).
650 0|a Mobile robots.|0 http://id.loc.gov/authorities/subjects/sh88005238
650 0|a Autonomous robots.|0 http://id.loc.gov/authorities/subjects/sh97006962
7001 |a Zdešar, Andrej,|e author.|0 http://id.loc.gov/authorities/names/no2017018059
7001 |a Blažič, Sašo,|e author.|0 http://id.loc.gov/authorities/names/no2017018559
7001 |a Škrjanc, Igor,|e author.|0 http://id.loc.gov/authorities/names/nb2013000338
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85640|u https://www.aclib.us/OReilly