Bøger i Control, Robotics and Sensors serien

The concept of swarm intelligence at first originated from the observation of nature. Through the observation and study of the behaviour of swarms of living creatures as ants colony, bird flocks, bees colony and fish school, inspired by the swarm/social phenomena exhibited by these biological swarms, the swarm of simple individuals through mutual cooperation shows up the emergence phenomena at the level of swarm, that is, 'the swarm of simple individuals shows the characteristics of complex intelligent behaviour through cooperation.'The swarm intelligence algorithms are characterised of simplicity, uncertainty, interactivity, distributed parallelism, robustness, scalability, and self-organisation. At present, the study of swarm intelligence algorithms mainly includes theory, algorithm and application. Its development trends include developing hybrid algorithms, new improved algorithms and theoretical analysis as well as solving large-scale problems (big data application). In general, swarm intelligence algorithms may shed a light on breaking the curse of no free lunches (NFLs), which shows that a deep study might give us enough anticipation motivating more and more researchers to engage in the research of swarm intelligence algorithms and their applications.Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will get inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.Volume 1 contains 20 chapters and presents the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimisation (PSO), ant colony optimisation (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics.With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence working in the fields of computer science, information technology, artificial intelligence, neural networks, computational intelligence, bioengineering, physics, mathematics, and social sciences.

Written by an international team of experts from a wide range of research areas, this book highlights the emerging role of cognitive sensors in a growing number of real time applications including smart health, smart cities, smart transportation, smart energy and smart agriculture.

This book covers important advances in the area of human-robot collaboration, aiming at future industrial applications. It will be useful to advanced students, researchers, engineers and entrepreneurs working on human-robot collaboration research and technologies, and related fields.

This book takes the reader through the development of a Ground Penetrating Radar (GPR) system, stressing the parameters that can be optimized and explaining the theory behind the GPR assessment. The authors provide a detailed discussion of the support tools and the numerical modeling of the system to improve readings from GPR systems.

This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS).

Thoroughly updated, revised and expanded, this second edition of a popular textbook now includes much more material on chemical sensors and chemical-biological sensors. It focuses on recent developments including Radar and Lidar sensors, lightning detector sensors, gunshot detector sensors, and more.

This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS).

This book focuses on the technologies constituting the IoT from a sensor perspective, for an audience of researchers, scientists, engineers and graduate students with an interest in the field. Applications covered include connected sensors for smart cities, energy infrastructure, emergency management, and smart ports.

Radar technology allows for touchless wireless gesture sensing by transmitting radio frequency (RF) signals to the target, accurately detecting gestures for Human Computer Interaction (HCI). Led by researchers from Google's Project Soli, the authors introduce the concept and underpinning technology.

Using important examples, this book showcases the potential of the latest data-based and data-driven methodologies for filter and control design. It discusses the most important classes of dynamic systems, along with the statistical and set membership analysis and design frameworks.

This book describes the advanced tools required to design state-of-the-art inference algorithms for inference in wireless sensor networks. Written for the signal processing, communications, sensors and information fusion research communities, it covers the emerging area of data fusion in wireless sensor networks.

This book provides a framework of different modeling and control algorithms using MATLAB®/Simulink®, and presents design, simulation and experimental verification techniques for the design of lower cost and more reliable and performant systems.

Industrial machines, automobiles, airplanes, robots, and machines are among the myriad possible hosts of embedded systems. This book has been prepared for those who seek to easily develop and design embedded systems for control purposes in robotic vehicles.

This book addresses the design challenges of developing and implementing novel integrated fault diagnosis and control technologies for complex linear systems.

This book introduces signal processing and machine learning techniques for BMI/BCI and outline their practical and future applications in neuroscience, medicine, and rehabilitation, with a focus on EEG-based BMI/BCI methods and technologies.

This book focuses on electromagnetic NDT methods and more specifically on the motion induced eddy current testing and evaluation (MIECTE) techniques used for conductive materials via electromagnetic methods, focusing on the Lorentz force eddy current testing (LET) method which was introduced recently.

Adaptive Sampling with Mobile WSN develops algorithms for optimal estimation of environmental parametric fields.

This edited book covers space robotics and autonomous systems (space RAS) from technologies to advances and applications including sensing and perception, mobility, manipulations, high-level autonomy, human-robot interaction, multi-modal interaction, modelling and simulation, and safety and trust.

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.Volume 2 includes 17 chapters covering front-edge research with novel and newly proposed algorithms and methods.With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.

Robust control theory allows for changes in a system whilst maintaining stability and performance. Applications of this technique are very important for dependable embedded systems, making technologies such as drones and other autonomous systems with sophisticated embedded controllers and systems relatively common-place.The aim of this book is to present the theoretical and practical aspects of embedded robust control design and implementation with the aid of MATLAB® and SIMULINK®. It covers methods suitable for practical implementations, combining knowledge from control system design and computer engineering to describe the entire design cycle. Three extended case studies are developed in depth: embedded control of a tank physical model; robust control of a miniature helicopter; and robust control of two-wheeled robots.These are taken from the area of motion control but the book may be also used by designers in other areas. Some knowledge of Linear Control Theory is assumed and knowledge of C programming is desirable but to make the book accessible to engineers new to the field and to students, the authors avoid complicated mathematical proofs and overwhelming computer architecture technical details. All programs used in the examples and case studies are freely downloadable to help with the assimilation of the book contents.