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"Presents a solid framework for understanding existing work and planning future research."--Cover.
Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed. Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.
The book is intended for advanced students in physics, mathematics, computer science, electrical engineering, robotics, engine engineering and for specialists in computer vision and robotics on the techniques for the development of vision-based robot projects. It focusses on autonomous and mobile service robots for indoor work, and teaches the techniques for the development of vision-based robot projects. A basic knowledge of informatics is assumed, but the basic introduction helps to adjust the knowledge of the reader accordingly. A practical treatment of the material enables a comprehensive understanding of how to handle specific problems, such as inhomogeneous illumination or occlusion. With this book, the reader should be able to develop object-oriented programs and show mathematical basic understanding. Such topics as image processing, navigation, camera types and camera calibration structure the described steps of developing further applications of vision-based robot projects.
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 textbook offers a tutorial introduction to robotics and Computer Vision which is light and easy to absorb. The practice of robotic vision involves the application of computational algorithms to data. Over the fairly recent history of the fields of robotics and computer vision a very large body of algorithms has been developed. However this body of knowledge is something of a barrier for anybody entering the field, or even looking to see if they want to enter the field — What is the right algorithm for a particular problem?, and importantly: How can I try it out without spending days coding and debugging it from the original research papers? The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provide a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used —instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals light and color, camera modelling, image processing, feature extraction and multi-view geometry, and bring it all together in a visual servo system. “An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished Oussama Khatib, Stanford
Industrial Assembly is a rapidly changing field with significant importance in production. This book is the first of its kind to combine technology, design, methods, and planning and control models of assembly operations and systems. With the increasing importance of assembly in industry and of simultaneous engineering approaches, this timely publication provides: comprehensive coverage of technological, engineering, and management aspects of this field; multi-disciplinary approaches to rationalization of assembly operations and systems; explanation of qualitative models, information technologies, and design techniques, which have been practised effectively in industrial assembly; as well as theoretical foundations and emerging trends that shape the future of assembly.
This book provides current research on robotics. The first chapter focuses on robot visual perception for object detection and recognition. Chapter Two discusses recent progress in vision-based robotics. Chapter Three examines portrait vision fusion. Chapter Four presents a preliminary design and experimental results of sex recognition. Chapter Five introduces the significance and application of health monitoring methods, and some of the traditional health monitoring methods are introduced. Chapter Six presents a systematic review of upper arm exoskeletons to find out under what clinical conditions use of such devices may be beneficial, what could be the technical requirements and what user interface must be provided to enhance their acceptability.
This book gathers the Proceedings of the International Conference on Mechatronics and Intelligent Robotics (ICMIR2017), held in Kunming, China, on May 20–21, 2017. The book covers a total of 172 papers, which have been divided into seven different sections: Intelligent Systems, Intelligent Sensors & Actuators, Robotics, Mechatronics, Modeling & Simulation, Automation & Control, and Robot Vision. ICMIR2017 provided a vital forum for discussing the latest and most innovative ideas from both the industrial and academic worlds, and for sharing best practices in the fields of mechanical engineering, mechatronics, automatic control, electrical engineering, finite element analysis and computational engineering. The main focus of the conference was on promoting interaction between academia and industry, allowing the free exchange of ideas and challenges faced by these two key stakeholders and encouraging future collaboration between the members of these groups. The proceedings cover new findings in the following areas of research and will offer readers valuable insights: Mechatronics Intelligent mechatronics, robotics and biomimetics; Novel and unconventional mechatronic systems; Modeling and control of mechatronics systems; Elements, structures and mechanisms of micro and nano systems; Sensors, wireless sensor networks and multi-sensor data fusion; Biomedical and rehabilitation engineering, prosthetics and artificial organs; Artificial Intelligence (AI), neural networks and fuzzy logic in mechatronics and robotics; Industrial automation, process control and networked control systems; Telerobotics, Human–Computer Interaction; and Human–Robot Interaction. Robotics Artificial Intelligence; Bio-inspired robotics; Control algorithms and control systems; Design theories and principles; Evolutional robotics; Field robotics; Force sensors, accelerometers, and other measuring devices; Healthcare robotics; Human–Robot Interaction; Kinematics and dynamics analysis; Manufacturing robotics; Mathematical and computational methodologies in robotics; Medical robotics; Parallel robots and manipulators; Robotic cognition and emotion; Robotic perception and decisions; Sensor integration, fusion, and perception; and Social robotics.
AI is poised to disrupt our work and our lives. We can harness these technologies rather than fall captive to them—but only through wise regulation. Too many CEOs tell a simple story about the future of work: if a machine can do what you do, your job will be automated. They envision everyone from doctors to soldiers rendered superfluous by ever-more-powerful AI. They offer stark alternatives: make robots or be replaced by them. Another story is possible. In virtually every walk of life, robotic systems can make labor more valuable, not less. Frank Pasquale tells the story of nurses, teachers, designers, and others who partner with technologists, rather than meekly serving as data sources for their computerized replacements. This cooperation reveals the kind of technological advance that could bring us all better health care, education, and more, while maintaining meaningful work. These partnerships also show how law and regulation can promote prosperity for all, rather than a zero-sum race of humans against machines. How far should AI be entrusted to assume tasks once performed by humans? What is gained and lost when it does? What is the optimal mix of robotic and human interaction? New Laws of Robotics makes the case that policymakers must not allow corporations or engineers to answer these questions alone. The kind of automation we get—and who it benefits—will depend on myriad small decisions about how to develop AI. Pasquale proposes ways to democratize that decision making, rather than centralize it in unaccountable firms. Sober yet optimistic, New Laws of Robotics offers an inspiring vision of technological progress, in which human capacities and expertise are the irreplaceable center of an inclusive economy.
This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.