Robotics, Vision and Control

Springer Tracts in Advanced Robotics

Book 118
Springer
Free sample

Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. The research community has developed a large body of such algorithms but for a newcomer to the field this can be quite daunting. For over 20 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and computer vision. It is written in an accessible but informative style, easy to read and absorb, and includes over 1000 MATLAB and Simulink® examples and over 400 figures. The book is a real walk through the fundamentals of mobile robots, arm robots. then camera models, image processing, feature extraction and multi-view geometry and finally bringing it all together with an extensive discussion of visual servo systems. This second edition is completely revised, updated and extended with coverage of Lie groups, matrix exponentials and twists; inertial navigation; differential drive robots; lattice planners; pose-graph SLAM and map making; restructured material on arm-robot kinematics and dynamics; series-elastic actuators and operational-space control; Lab color spaces; light field cameras; structured light, bundle adjustment and visual odometry; and photometric visual servoing.

“An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished!”

OUSSAMA KHATIB, Stanford

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About the author

The author is the organizer of the venerable Robotics Toolbox for Matlab http://www.petercorke.com/robot with 100.000 + downloads per year (as well as the Vision Toolbox for Matlab)

Peter Corke has been appointed new Editor of the IEEE Robotics and Automation Magazine.

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Additional Information

Publisher
Springer
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Published on
May 20, 2017
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Pages
693
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ISBN
9783319544137
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Language
English
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Genres
Computers / Computer Graphics
Computers / Intelligence (AI) & Semantics
Computers / Optical Data Processing
Psychology / Cognitive Psychology & Cognition
Technology & Engineering / Automation
Technology & Engineering / Electronics / General
Technology & Engineering / Imaging Systems
Technology & Engineering / Manufacturing
Technology & Engineering / Robotics
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Content Protection
This content is DRM protected.
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This monograph introduces a unifying framework for mapping, planning and exploration with mobile robots considering uncertainty, linking such problems with a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are used to produce relative motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this monograph covers the study of such measurements when they are obtained with stereo cameras, develops the appropriate noise propagation models for such case, extends the Pose SLAM formulation to SE(3), introduces information-theoretic loop closure tests, and presents a technique to compute traversability maps from the 3D volumetric maps obtained with Pose SLAM. A relevant topic covered in this monograph is the introduction of a novel path planning approach that exploits the modeled uncertainties in Pose SLAM to search for the path in the pose graph that allows the robot to navigate to a given goal with the least probability of becoming lost. Another relevant topic is the introduction of an autonomous exploration method that selects the appropriate actions to drive the robot so as to maximize coverage, while minimizing localization and map uncertainties. This monograph is appropriate for readers interested in an information-theoretic unified perspective to the SLAM, path planning and exploration problems, and is a reference book for people who work in mobile robotics research in general.
Cable-driven parallel robots are a new kind of lightweight manipulators with excellent scalability in terms of size, payload, and dynamics capacities. For the first time, a comprehensive compendium is presented of the field of cable-driven parallel robots. A thorough theory of cable robots is setup leading the reader from first principles to the latest results in research.

The main topics covered in the book are classification, terminology, and fields of application for cable-driven parallel robots. The geometric foundation of the standard cable model is introduced followed by statics, force distribution, and stiffness. Inverse and forward kinematics are addressed by elaborating efficient algorithms. Furthermore, the workspace is introduced and different algorithms are detailed. The book contains the dynamic equations as well as simulation models with applicable parameters. Advanced cable models are described taking into account pulleys, elastic cables, and sagging cables.

For practitioner, a descriptive design method is stated including methodology, parameter synthesis, construction design, component selection, and calibration. Rich examples are presented by means of simulation results from sample robots as well as experimental validation on reference demonstrators. The book contains a representative overview of reference demonstrator system. Tables with physical parameters for geometry, cable properties, and robot parameterizations support case studies and are valuable references for building custom cable robots.

For scientist, the book provides the starting point to address new scientific challenges as open problems are named and a commented review of the literature on cable robot with more than 500 references are given.

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”.

The field of robotic vision has advanced dramatically recently with the development of new range sensors. Tremendous progress has been made resulting in significant impact on areas such as robotic navigation, scene/environment understanding, and visual learning. This edited book provides a solid and diversified reference source for some of the most recent important advancements in the field of robotic vision. The book starts with articles that describe new techniques to understand scenes from 2D/3D data such as estimation of planar structures, recognition of multiple objects in the scene using different kinds of features as well as their spatial and semantic relationships, generation of 3D object models, approach to recognize partially occluded objects, etc. Novel techniques are introduced to improve 3D perception accuracy with other sensors such as a gyroscope, positioning accuracy with a visual servoing based alignment strategy for microassembly, and increasing object recognition reliability using related manipulation motion models. For autonomous robot navigation, different vision-based localization and tracking strategies and algorithms are discussed. New approaches using probabilistic analysis for robot navigation, online learning of vision-based robot control, and 3D motion estimation via intensity differences from a monocular camera are described. This collection will be beneficial to graduate students, researchers, and professionals working in the area of robotic vision.

This monograph introduces a unifying framework for mapping, planning and exploration with mobile robots considering uncertainty, linking such problems with a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are used to produce relative motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this monograph covers the study of such measurements when they are obtained with stereo cameras, develops the appropriate noise propagation models for such case, extends the Pose SLAM formulation to SE(3), introduces information-theoretic loop closure tests, and presents a technique to compute traversability maps from the 3D volumetric maps obtained with Pose SLAM. A relevant topic covered in this monograph is the introduction of a novel path planning approach that exploits the modeled uncertainties in Pose SLAM to search for the path in the pose graph that allows the robot to navigate to a given goal with the least probability of becoming lost. Another relevant topic is the introduction of an autonomous exploration method that selects the appropriate actions to drive the robot so as to maximize coverage, while minimizing localization and map uncertainties. This monograph is appropriate for readers interested in an information-theoretic unified perspective to the SLAM, path planning and exploration problems, and is a reference book for people who work in mobile robotics research in general.
Cable-driven parallel robots are a new kind of lightweight manipulators with excellent scalability in terms of size, payload, and dynamics capacities. For the first time, a comprehensive compendium is presented of the field of cable-driven parallel robots. A thorough theory of cable robots is setup leading the reader from first principles to the latest results in research.

The main topics covered in the book are classification, terminology, and fields of application for cable-driven parallel robots. The geometric foundation of the standard cable model is introduced followed by statics, force distribution, and stiffness. Inverse and forward kinematics are addressed by elaborating efficient algorithms. Furthermore, the workspace is introduced and different algorithms are detailed. The book contains the dynamic equations as well as simulation models with applicable parameters. Advanced cable models are described taking into account pulleys, elastic cables, and sagging cables.

For practitioner, a descriptive design method is stated including methodology, parameter synthesis, construction design, component selection, and calibration. Rich examples are presented by means of simulation results from sample robots as well as experimental validation on reference demonstrators. The book contains a representative overview of reference demonstrator system. Tables with physical parameters for geometry, cable properties, and robot parameterizations support case studies and are valuable references for building custom cable robots.

For scientist, the book provides the starting point to address new scientific challenges as open problems are named and a commented review of the literature on cable robot with more than 500 references are given.

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