“Visual Sensing and its Applications: Integration of Laser Sensors to Industrial Robots” provides comprehensive and up-to-date coverage of research and development on this robotic vision system. A laser-structured light is the main concern in discussions of visual sensing. Also addressed in this book are all components of the robotic vision system and an emphasis on how to increase the accuracy of the system using three levels of calibration. This includes calibration of the vision system (eye calibration), calibration of eye-to-hand configuration and calibration of robot kinematics (hand calibration). With the integration of the laser sensors to industrial robots numerous applications in the field of robotic welding, grinding, machining, inspection, and palletizing are illustrated based on practical engineering projects in order to demonstrate how the visual sensing is performed. The book will serve as a valuable resource for researchers and engineers in the areas of robotics and machine vision. Dr. Zhongxue Gan is a vice chairman and chief scientist of the ENN Group, China. He serves as a member of the National Energy Expert Consultation Committee of China and member of the National Coal Council of the USA. He is also a co-founder of Intersmart Robotic Systems Co. Ltd., China. He was a research fellow in flexible automation systems at ABB and a founding director of ABB Corporate Research Robot Laboratories, both in the USA and in China. Dr. Qing Tang is a co-founder and CEO of Intersmart Robotic Systems Co. Ltd., China and an adjunct professor in Physics at Sichuan University, China. He was a principle consulting engineer and project manager at the ABB Corporate Research Robot Laboratory in the USA.

"This book provides a central source of reference on visual information processing in wireless sensor network environments and its technology, application, and society issues"--

Annotation Embedded vision systems such as smart cameras have been rapidly developed recently. Vision systems have become smaller and lighter, but their performance has improved. The algorithms in embedded vision systems have their specifications limited by frequency of CPU, memory size, and architecture. The goal of this e-book is to provide a an advanced reference work for engineers, researchers and scholars in the field of robotics, machine vision, and automation and to facilitate the exchange of their ideas, experiences and views on embedded vision system models. The effectiveness for all methods is emphasized in a practical sense for systems presented in this e-book.

Large-scale video networks are of increasing importance in a wide range of applications. However, the development of automated techniques for aggregating and interpreting information from multiple video streams in real-life scenarios is a challenging area of research. Collecting the work of leading researchers from a broad range of disciplines, this timely text/reference offers an in-depth survey of the state of the art in distributed camera networks. The book addresses a broad spectrum of critical issues in this highly interdisciplinary field: current challenges and future directions; video processing and video understanding; simulation, graphics, cognition and video networks; wireless video sensor networks, communications and control; embedded cameras and real-time video analysis; applications of distributed video networks; and educational opportunities and curriculum-development. Topics and features: presents an overview of research in areas of motion analysis, invariants, multiple cameras for detection, object tracking and recognition, and activities in video networks; provides real-world applications of distributed video networks, including force protection, wide area activities, port security, and recognition in night-time environments; describes the challenges in graphics and simulation, covering virtual vision, network security, human activities, cognitive architecture, and displays; examines issues of multimedia networks, registration, control of cameras (in simulations and real networks), localization and bounds on tracking; discusses system aspects of video networks, with chapters on providing testbed environments, data collection on activities, new integrated sensors for airborne sensors, face recognition, and building sentient spaces; investigates educational opportunities and curriculum development from the perspective of computer science and electrical engineering. This unique text will be of great interest to researchers and graduate students of computer vision and pattern recognition, computer graphics and simulation, image processing and embedded systems, and communications, networks and controls. The large number of example applications will also appeal to application engineers.

This book describes active illumination techniques in computer vision. We can classify computer vision techniques into two classes: passive and active techniques. Passive techniques observe the scene statically and analyse it as is. Active techniques give the scene some actions and try to facilitate the analysis. In particular, active illumination techniques project specific light, for which the characteristics are known beforehand, to a target scene to enable stable and accurate analysis of the scene. Traditional passive techniques have a fundamental limitation. The external world surrounding us is three-dimensional; the image projected on a retina or an imaging device is two-dimensional. That is, reduction of one dimension has occurred. Active illumination techniques compensate for the dimensional reduction by actively controlling the illumination. The demand for reliable vision sensors is rapidly increasing in many application areas, such as robotics and medical image analysis. This book explains this new endeavour to explore the augmentation of reduced dimensions in computer vision. This book consists of three parts: basic concepts, techniques, and applications. The first part explains the basic concepts for understanding active illumination techniques. In particular, the basic concepts of optics are explained so that researchers and engineers outside the field can understand the later chapters. The second part explains currently available active illumination techniques, covering many techniques developed by the authors. The final part shows how such active illumination techniques can be applied to various domains, describing the issue to be overcome by active illumination techniques and the advantages of using these techniques. This book is primarily aimed at 4th year undergraduate and 1st year graduate students, and will also help engineers from fields beyond computer vision to use active illumination techniques. Additionally, the book is suitable as course material for technical seminars.

This book aims to explore the latest practices and research works in the area of sensor fusion. The book intends to provide a collection of novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. This book is a unique, comprehensive, and up-to-date resource for sensor fusion systems designers. This book is appropriate for use as an upper division undergraduate or graduate level text book. It should also be of interest to researchers, who need to process and interpret the sensor data in most scientific and engineering fields. The initial chapters in this book provide a general overview of sensor fusion. The later chapters focus mostly on the applications of sensor fusion. Much of this work has been published in refereed journals and conference proceedings and these papers have been modified and edited for content and style. With contributions from the world's leading fusion researchers and academicians, this book has 22 chapters covering the fundamental theory and cutting-edge developments that are driving this field.

The proceeding is a collection of research papers presented at the 11th International Conference on Robotics, Vision, Signal Processing & Power Applications (RoViSP 2021). The theme of RoViSP 2021 “Enhancing Research and Innovation through the Fourth Industrial Revolution (IR 4.0)” served as a platform for researchers, scientists, engineers, academicians as well as industrial professionals from all around the globe to present and exchange their research findings and development activities through oral presentations. The book covers various topics of interest, including: Robotics, Control, Mechatronics and Automation Telecommunication Systems and Applications Electronic Design and Applications Vision, Image and Signal Processing Electrical Power, Energy and Industrial Applications Computer and Information Technology Biomedical Engineering and Applications Intelligent Systems Internet-of-things Mechatronics Mobile Technology

Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.

Contains the latest research, case studies, theories, and methodologies within the field of wireless technologies.

The Internet of Things (IoT) has numerous applications, including smart cities, industries, cloud-based apps, smart homes, and surveillance. The Internet of Things (IoT) enables smarter living by connecting devices, people, and objects. As networking became a crucial aspect of the Internet, rigorous design analysis led to the development of new research areas. The Internet of Things has revolutionized daily living in countless ways. It enables communication between buildings, people, portable gadgets, and vehicles, facilitating mobility. Smart cities and cloud-based data have transformed corporate practices. With billions of connected gadgets, everything will soon be able to communicate remotely. IoT networks, whether public or private, rely significantly on machine learning and software-defined networking. Indian and other governments have approved various research projects on IoT-based networking technologies. This field of study will significantly impact society in the future. Researchers are concerned about the many application areas and driving forces behind smart cities. The authors aim to provide insights into software-defined networking, artificial intelligence, and machine learning technologies used in IoT and networking. The framework focuses on practical applications and infrastructures. The book includes practical challenges, case studies, innovative concepts, and other factors that impact the development of realistic scenarios for smart surveillance. It also highlights innovative technology, designs, and algorithms that can accelerate the creation of smart city concepts. This resource includes real-world applications and case studies for smart city technology, enormous data management, and machine learning prediction, all with confidentiality and safety problems.