The great majority of books on artificial intelligence are written by AI experts who understandably focus on its achievements and potential transformative effects on society. In contrast, AI vs Humans is written by two psychologists (Michael and Christine Eysenck) whose perspective on AI (including robotics) is based on their knowledge and understanding of human cognition. This book evaluates the strengths and limitations of people and AI. The authors' expertise equips them well to consider this by seeing how well (or badly) AI compares to human intelligence. They accept that AI matches or exceeds human ability in many spheres such as mathematical calculations, complex games (e.g., chess, Go, and poker), diagnosis from medical images, and robotic surgery. However, the human tendency to anthropomorphise has led many people to claim mistakenly that AI systems can think, infer, reason, and understand while engaging in information processing. In fact, such systems lack all those cognitive skills and are also deficient in the quintessentially human abilities of flexibility of thinking and general intelligence. At a time when human commitment to AI appears unstoppable, this up-to-date book advocates a symbiotic and co-operative relationship between humans and AI. It will be essential reading for anyone interested in AI and human cognition.

Universal vehicular communication promises many improvements in terms of ac- dent avoidance and mitigation, better utilization of roads and resources such as time and fuel, and new opportunities for infotainment applications. However, before widespread acceptance, vehicular communication must meet challenges comparable to the trouble and disbelief that accompanied the introduction of traf c lights back then. The rst traf c light was installed in 1868 in London to signal railway, but only later, in 1912, was invented the rst red-green electric traf c light. And roughly 50 years after the rst traf c light, in 1920, the rst four-way traf c signal comparable to our today's traf c lights was introduced. The introduction of traf c signals was necessary after automobiles soon became prevalent once the rst car in history, actually a wooden motorcycle, was constructed in 1885. Soon, the scene became complicated, requiring the introduction of the "right-of-way" philosophy and later on the very rst traf c light. In the same way the traf c light was a necessary mean to regulate the beginning of the automotive life and to protect drivers, passengers, as well as pedestrians and other inhabitants of the road infrastructure, vehicular communication is necessary to accommodate the further growth of traf c volume and to signi cantly reduce the number of accidents.

Fact finding in judicial proceedings is a dynamic process. This collection of papers considers whether computational methods or other formal logical methods developed in disciplines such as artificial intelligence, decision theory, and probability theory can facilitate the study and management of dynamic evidentiary and inferential processes in litigation. The papers gathered here have several epicenters, including (i) the dynamics of judicial proof, (ii) the relationship between artificial intelligence or formal analysis and "common sense," (iii) the logic of factual inference, including (a) the relationship between causality and inference and (b) the relationship between language and factual inference, (iv) the logic of discovery, including the role of abduction and serendipity in the process of investigation and proof of factual matters, and (v) the relationship between decision and inference.

"Software Engineering for Experimental Robotics" collects contributions that describe the state of the art in software development for the Robotics domain. It reports on innovative ideas that are progressively introduced in the software development process, in order to promote the reuse of robotic software artifacts: domain engineering, components, frameworks and architectural styles. It illustrates the results of the most successful and well-known research projects which aim to develop reusable robotic software systems. Most of the chapters report on concepts and ideas discussed at the well attended ICRA2005 Workshop on "Principles and Practice of Software Development in Robotics," Barcelona, Spain, April 18 2005. The authors are recognised as leading scholars internationally, and the result is an effective blend of fundamental and innovative results on research and development in software for robotic systems, where one common factor is the integration of reusable building blocks. Besides the advancement in the field, most contributions survey the state of the art, report a number of practical applications to real systems, and discuss possible future developments.

Aerial Robotic Workers: Design, Modeling, Control, Vision and Their Applications provides an in-depth look at both theory and practical applications surrounding the Aerial Robotic Worker (ARW). Emerging ARWs are fully autonomous flying robots that can assist human operations through their agile performance of aerial inspections and interaction with the surrounding infrastructure. This book addresses all the fundamental components of ARWs, starting with the hardware and software components and then addressing aspects of modeling, control, perception of the environment, and the concept of aerial manipulators, cooperative ARWs, and direct applications. The book includes sample codes and ROS-based tutorials, enabling the direct application of the chapters and real-life examples with platforms already existing in the market.

Roboticsis undergoingamajortransformationinscopeanddimension.From a largelydominantindustrialfocus,roboticsis rapidly expandinginto human environments and vigorouslyengaged in its new challenges. Interacting with, assisting, serving, and exploring with humans, the emerging robots will - creasingly touch people and their lives. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across - verse research areas and scienti?c disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are pr- ing an abundant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. TheSpringerTractsinAdvancedRobotics(STAR)isdevotedtobringingto the research community the latest advances in the robotics ?eld on the basis of their signi?cance and quality. Through a wide and timely dissemination of critical research developments in robotics, our objective with this series is to promotemoreexchangesandcollaborationsamongtheresearchersinthec- munity and contributeto further advancements inthis rapidlygrowing?eld. The monographwritten byAlejandro DizanVasquez Goveafocusesonthe practicalproblem of moving in a cluttered environment with pedestrians and vehicles. A frameworkbased on Hidden Markov models is developed to learn typical motion patterns which can be used to predict motion on the basis of sensor data. All the theoretical results have been implemented and validated with experiments, using both real and simulated data.

Neuro-robotics is one of the most multidisciplinary fields of the last decades, fusing information and knowledge from neuroscience, engineering and computer science. This book focuses on the results from the strategic alliance between Neuroscience and Robotics that help the scientific community to better understand the brain as well as design robotic devices and algorithms for interfacing humans and robots. The first part of the book introduces the idea of neuro-robotics, by presenting state-of-the-art bio-inspired devices. The second part of the book focuses on human-machine interfaces for performance augmentation, which can seen as augmentation of abilities of healthy subjects or assistance in case of the mobility impaired. The third part of the book focuses on the inverse problem, i.e. how we can use robotic devices that physically interact with the human body, in order (a) to understand human motor control and (b) to provide therapy to neurologically impaired people or people with disabilities.

Vision-based mobile robot guidance has proved difficult for classical machine vision methods because of the diversity and real-time constraints inherent in the task. This book describes a connectionist system called ALVINN (Autonomous Land Vehicle In a Neural Network) that overcomes these difficulties. ALVINN learns to guide mobile robots using the back-propagation training algorithm. Because of its ability to learn from example, ALVINN can adapt to new situations and therefore cope with the diversity of the autonomous navigation task. But real world problems like vision-based mobile robot guidance present a different set of challenges for the connectionist paradigm. Among them are: how to develop a general representation from a limited amount of real training data; how to understand the internal representations developed by artificial neural networks; how to estimate the reliability of individual networks; how to combine multiple networks trained for different situations into a single system; how to combine connectionist perception with symbolic reasoning. Neural Network Perception for Mobile Robot Guidance presents novel solutions to each of these problems. Using these techniques, the ALVINN system can learn to control an autonomous van in under 5 minutes by watching a person drive. Once trained, individual ALVINN networks can drive in a variety of circumstances, including single-lane paved and unpaved roads, and multi-lane lined and unlined roads, at speeds of up to 55 miles per hour. The techniques also are shown to generalize to the task of controlling the precise foot placement of a walking robot.

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand's functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand's function for grasping and manipulation of everyday life objects. This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is the central issue. In the first part of the book, aspects of learning in execution and control are discussed. Methods for the automatic synthesis of controllers, for active sensing, for learning to enhance assembly, and for learning sensor-based navigation are presented. Since robots are not isolated but should serve us, the second part of the book discusses learning for human-robot interaction. Methods of learning understandable concepts for assembly, monitoring, and navigation are described as well as optimizing the implementation of such understandable concepts for a robot's real-time performance. In terms of the study of embodied intelligence, Making Robots Smarter asks how skills are acquired and where capabilities of execution and control come from. Can they be learned from examples or experience? What is the role of communication in the learning procedure? Whether we name it one way or the other, the methodological challenge is that of integrating learning capabilities into robots.

Here is a comprehensive presentation of methodology for the design and synthesis of an intelligent complex robotic system, connecting formal tools from discrete system theory, artificial intelligence, neural network, and fuzzy logic. The necessary methods for solving real time action planning, coordination and control problems are described. A notable chapter presents a new approach to intelligent robotic agent control acting in a realworld environment based on a lifelong learning approach combining cognitive and reactive capabilities. Another key feature is the homogeneous description of all solutions and methods based on system theory formalism.

The present book includes a set of selected papers from the seventh "International Conference on Informatics in Control Automation and Robotics" (ICINCO 2010), held in Madeira, Portugal, from 15 to 18 June 2010. The conference was organized in three simultaneous tracks: "Intelligent Control Systems and Optimization", "Robotics and Automation" and "Signal Processing, Systems Modeling and Control". The book is based on the same structure. ICINCO received 320 paper submissions, not including those of workshops or special sessions, from 57 countries, in all continents. After a double blind paper review performed by the Program Committee only 27 submissions were accepted as full papers and thus selected for oral presentation, leading to a full paper acceptance ratio of 8%. Additional papers were accepted as short papers and posters. A further refinement was made after the conference, based also on the assessment of presentation quality, so that this book includes the extended and revised versions of the very best papers of ICINCO 2010. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions of this conference, including not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, workshops and logistics.

Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain provides imperative research on the development of data fusion and analytics for healthcare and their implementation into current issues in a real-time environment. While highlighting IoT, bio-inspired computing, big data, and evolutionary programming, the book explores various concepts and theories of data fusion, IoT, and Big Data Analytics. It also investigates the challenges and methodologies required to integrate data from multiple heterogeneous sources, analytical platforms in healthcare sectors. This book is unique in the way that it provides useful insights into the implementation of a smart and intelligent healthcare system in a post-Covid-19 world using enabling technologies like Artificial Intelligence, Internet of Things, and blockchain in providing transparent, faster, secure and privacy preserved healthcare ecosystem for the masses.

This book presents the concept of cognition in a clear, lucid and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms, and demonstrates their application with real life experiments.

This book introduces a comprehensive and mathematically rigorous controller design for families of nonlinear systems with time-varying parameters and unstructured uncertainties. Although the presented methodology is general, the specific family of systems considered is the latest, NextGen, unconventional fixed-wing unmanned aircraft with circulation control or morphing wings, or a combination of both. The approach considers various sources of model and parameter uncertainty, while the controller design depends not on a nominal plant model, but instead on a family of admissible plants. In contrast to existing controller designs that consider multiple models and multiple controllers, the proposed approach is based on the 'one controller fits all models' within the unstructured uncertainty interval. The book presents a modeling-based analysis and synthesis approach with additive uncertainty weighting functions for accurate realization of the candidate systems. This differs significantly from existing designs in that it is capable of handling time-varying characteristics. This research monograph is suitable for scientists, engineers, researchers and graduate students with a background in control system theory who are interested in complex engineering nonlinear systems.

This volume describes new frontiers in medical and service robotics in the light of recent developments in technology to advance robot design and implementation. In particular, the work looks at advances in design, development and implementation of contemporary surgical, rehabilitation and biorobots. Surgical robots allow surgeons greater access to areas under operation using more precise and less invasive methods. Rehabilitation robots facilitate and support the lives of the infirm, elderly people, or those with dysfunction of body parts affecting movement. These robots are also used for rehabilitation and related procedures, such as training and therapy. Biorobots are designed to imitate the cognition of humans and animals. The need to substitute humans working on delicate, tiresome and monotonous tasks, or working with potentially health-damaging toxic materials, requires intelligent, high-performance service robots with the ability to cooperate, advanced communication and sophisticated perception and cognitive capabilities. Progress in this field is fast and results need to be disseminated to stimulate both practical applications and further research. Thus, these papers are a valuable addition to existing literature.

Verification presents the most time-consuming task in the integrated circuit design process. The increasing similarity between implementation verification and the ever-needed task of providing vectors for manufacturing fault testing is tempting many professionals to combine verification and testing efforts.
This book presents the basis for reusing the test vector generation and simulation for the purpose of implementation verification, to result in a significant timesaving. The book brings the results in the direction of merging manufacturing test vector generation and verification. It first discusses error fault models suitable for approaching the verification by testing methods. Then, it elaborates a proposal for an implicit fault model that uses the Arithmetic Transform representation of a circuit and the faults. Presented is the fundamental link between the error size and the test vector size, which allows parametrizable verification by test vectors. Furthermore, the test vector set is sufficient not only for detecting, but also for diagnosing and correcting the design errors.
The practical use of any such simulation-based verification scheme can be seriously impaired by redundant faults, that otherwise require exhaustive simulations. The redundant fault identification methods are presented that are well suited for the type of faults considered. Finally, the same representation can be used to augment and expand the formal verification schemes that are to be used in conjunction with the simulation-based verification.
The primary audience for Verification by Error Modeling includes researchers in verification and testing, managers in charge of verification of test andpracticing engineers. Due to its comprehensive coverage of background topics, the book can also be used for teaching courses on verification and test topics.

Nowadays, multiple attention have been paid on a robot working in the human living environment, such as in the field of medical, welfare, entertainment and so on. Various types of researches are being conducted actively in a variety of fields such as artificial intelligence, cognitive engineering, sensor- technology, interfaces and motion control. In the future, it is expected to realize super high functional human-like robot by integrating technologies in various fields including these types of researches. The book represents new developments and advances in the field of bio-inspired robotics research introducing the state of the art, the idea of multi-locomotion robotic system to implement the diversity of animal motion. It covers theoretical and computational aspects of Passive Dynamic Autonomous Control (PDAC), robot motion control, multi legged walking and climbing as well as brachiation focusing concrete robot systems, components and applications. In addition, gorilla type robot systems are described as hardware of Multi-Locomotion Robotic system. It is useful for students and researchers in the field of robotics in general, bio-inspired robots, multi-modal locomotion, legged walking, motion control, and humanoid robots. Furthermore, it is also of interest for lecturers and engineers in practice building systems cooperating with humans.

This book presents the latest scientific research related to the field of Robotics. It involves different topics such as biomedicine, energy efficiency and home automationand robotics.

The book is written bytechnical experts and researchers from academia and industry working on robotics applications. The book could be used as supplementary material for courses related to Robotics and Domotics. "

In 1960, R. E. Kalman published his celebrated paper on recursive min imum variance estimation in dynamical systems [14]. This paper, which introduced an algorithm that has since been known as the discrete Kalman filter, produced a virtual revolution in the field of systems engineering. Today, Kalman filters are used in such diverse areas as navigation, guid ance, oil drilling, water and air quality, and geodetic surveys. In addition, Kalman's work led to a multitude of books and papers on minimum vari ance estimation in dynamical systems, including one by Kalman and Bucy on continuous time systems [15]. Most of this work was done outside of the mathematics and statistics communities and, in the spirit of true academic parochialism, was, with a few notable exceptions, ignored by them. This text is my effort toward closing that chasm. For mathematics students, the Kalman filtering theorem is a beautiful illustration of functional analysis in action; Hilbert spaces being used to solve an extremely important problem in applied mathematics. For statistics students, the Kalman filter is a vivid example of Bayesian statistics in action. The present text grew out of a series of graduate courses given by me in the past decade. Most of these courses were given at the University of Mas sachusetts at Amherst.