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Thanks to advances in sensing and computer vision technologies, robots can be found today in healthcare, medicine and the industry. Topics covered in this edited book include various types of sensors used in robotics, sensing schemes, sensing technologies and their applications including robotics, prosthetics, wearables and healthcare. Written for those working in robotics, sensor technologies and electronics, and their applications in robotics, haptics, prosthetics, wearable and interactive systems, cognitive engineering, neuro-engineering, computational neuroscience, medicine, and healthcare technologies.

Focusing on autonomous robotic applications, this cutting-edge resource offers you a practical treatment of short-range radar processing for reliable object detection at the ground level. This unique book demonstrates probabilistic radar models and detection algorithms specifically for robotic land vehicles. It examines grid based robotic mapping with radar based on measurement likelihood estimation. You find detailed coverage of simultaneous localization and Map Building (SLAM) - an area referred to as the Holy Grailù of autonomous robotic research. The book derives an extended Kalman Filter SLAM algorithm which exploits the penetrating ability of radar. This algorithm allows for the observation of visually occluded objects, as well as the usual directly observed objects, which contributes to a robot 's position and the map state update. Moreover, you discover how the Random Finite Set (RFS) provides a more appropriate approach for representing radar based maps than conventional frameworks.

The 24 chapters in this book provides a deep overview of robotics and the application of AI and IoT in robotics.It contains the exploration of AI and IoT based intelligent automation in robotics.The various algorithms and frameworks for robotics based on AI and IoT are presented, analyzed, and discussed.

The idea of autonomous systems that are able to make choices according to properties which allow them to experience, apprehend and assess their environment is becoming a reality. These systems are capable of auto-configuration and self-organization. This book presents a model for the creation of autonomous systems based on a complex substratum, made up of multiple electronic components that deploy a variety of specific features. This substratum consists of multi-agent systems which act continuously and autonomously to collect information from the environment which they then feed into the global system, allowing it to generate discerning and concrete representations of its surroundings. These systems are able to construct a so-called artificial corporeity which allows them to have a sense of self, to then behave autonomously, in a way reminiscent of living organisms.

This book explores an approach to social robotics based solely on autonomous unsupervised techniques and positions it within a structured exposition of related research in psychology, neuroscience, HRI, and data mining. The authors present an autonomous and developmental approach that allows the robot to learn interactive behavior by imitating humans using algorithms from time-series analysis and machine learning. The first part provides a comprehensive and structured introduction to time-series analysis, change point discovery, motif discovery and causality analysis focusing on possible applicability to HRI problems. Detailed explanations of all the algorithms involved are provided with open-source implementations in MATLAB enabling the reader to experiment with them. Imitation and simulation are the key technologies used to attain social behavior autonomously in the proposed approach. Part two gives the reader a wide overview of research in these areas in psychology, and ethology. Based on this background, the authors discuss approaches to endow robots with the ability to autonomously learn how to be social. Data Mining for Social Robots will be essential reading for graduate students and practitioners interested in social and developmental robotics.

This documentary, produced by Mark Horstman, is about a competition for autonomous robots.

In the not so distant future, we can expect a world where humans and robots coexist and interact with each other. For this to occur, we need to understand human traits, such as seeing, hearing, thinking, speaking, etc., and institute these traits in robots. The most essential feature necessary for robots to achieve is that of integrative multimedia understanding (IMU) which occurs naturally in humans. It allows us to assimilate pieces of information expressed through different modes such as speech, pictures, gestures, etc. The book describes how robots acquire traits like natural language understanding (NLU) as the central part of IMU. Mental image directed semantic theory (MIDST) is its core, and is based on the hypothesis that NLU is essentially the processing of mental image associated with natural language expressions, namely, mental-image based understanding (MBU). MIDST is intended to model omnisensory mental image in human and to afford a knowledge representation system in order for integrative management of knowledge subjective to cognitive mechanisms of intelligent entities such as humans and robots based on a mental image model visualized as ‘Loci in Attribute Spaces’ and its description language L md (mental image description language) to be employed for predicate logic with a systematic scheme for symbol-grounding. This language works as an interlingua among various kinds of information media, and has been applied to several versions of the intelligent system interlingual understanding model aiming at general system (IMAGES). Its latest version, i.e. conversation management system (CMS) simulates MBU and comprehends the user’s intention through dialogue to find and solve problems, and finally, provides a response in text or animation. The book is aimed at researchers and students interested in artificial intelligence, robotics, and cognitive science. Based on philosophical considerations, the methodology will also have an appeal in linguistics, psychology, ontology, geography, and cartography. Key Features: Describes the methodology to provide robots with human-like capability of natural language understanding (NLU) as the central part of IMU Uses methodology that also relates to linguistics, psychology, ontology, geography, and cartography Examines current trends in machine translation Table of Contents: Introduction Anna - an ideal home robot Intuitive human-robot interaction Integrative multimedia understanding and natural language understanding Knowledge and cognition Natural Language Processing Viewed from Semantics Trends in machine translation Case study of current MT systems (as of October, 2018) Fundamentals for Robotic NLU NLU in accordance with semiotics Syntactic analysis Semantic analysis and pragmatic analysis Robust NLU Response synthesis Syntax and semantics of discourse Cognitive Essentials for Midst Functional model of human mind Human knowledge and cognitive propensities Semantics and mental image QSIs (quasi-symbolic images) and human concept system Primitive quasi-symbolic images Perception of causality Semantic articulation and QSI connectors Negation of mental image Imaginary space region Computational Model of Mental Image Atomic locus as primitive QSI Temporal conjunctions as QSI connectors Empty event Attributes and Standards Formal System Semantic principle of L md Syntax of L md Tempo-logical connectives Formulation of event concepts Formulation of laws of the world Fundamental Postulates and Inference Rules for Deductive System Properties of Loci Inference rules for deduction Tempo-logical deduction with TLCs 　 　 　 　 　 Human-Specific Semantics of 4d Language as Mental Images Conventional approaches to 4D language understanding 4D language semantics as mental images Formulation of concepts of spatial prepositions Properties of static 4D concepts as human intuitive mental images Reversal operation on spatial change event concepts as mental images Problem Finding and Solving in Formal System Definition of problem and task Creation problem finding and solving Maintenance problem finding and solving Human Language Understanding by Robots Two-staged robotic NLU Robotic concept system for iHRI Compound concept system for robots Robot manipulation as cross-media operation via L md Aware computing in robots Homogeneous/Inhomogeneous Communication 4d Language Understanding for Cognitive Robotics Requirements for robotic NLU Logical Adequacy of L md Translation between NL and L md Reasoning in L md Anchoring via L md Behavioralization via L md Systematic interpretation of L md Multilingual Operation Via L md Meaning definition Optimization of grammatical description for word meaning definition Language operation via L md Question answering through L md Computational Model of Japanese for NLU Brief description of basic Japanese Phrase structure grammar for Japanese Dependency grammar for Japanese Sentence and discourse of Japanese Sentence types of Japanese and phrasing Implementation of Mental-Image Based Understanding Configuration of CMS MBU versus conventional NLU Stimulus sentences to CMS and human subjects Mental image based understanding by CMS Problem finding and solving in CMS Awareness control of CMS Conclusions References 　 This is an excellent resource for scientists and engineers looking to develop a deep natural language understanding system for application in robotics, currently one of the most critical areas of development for artificial intelligence technologies. The book is very well written and easy to follow for readers with a good background in artificial intelligence or natural language processing. The considerable number of examples and diagrams included make this volume particularly valuable for students. The examples illustrating machine understanding of Japanese offer an exciting bonus for readers engaged in machine translation or computational linguistics. -- J. Brzezinski, McHenry County College, Choice, 2020 Vol. 58 No. 2 Masao Yokota received a Bachelor degree from Kyushu Institute of Technology, and Master and Doctor degrees from Kyushu University. He is now a professor of informatics at Fukuoka Institute of Technology. His research focus is on AI, especially in integrative multimedia understanding by robots in being as 'natural' as humans where natural language understanding (NLU) plays the central role. He has proposed 'Mental Image Directed Semantic Theory (MIDST)' based on a hypothesis that NLU in humans is mental image processing. MIDST provides an omnisensory mental image model and a formal language called ' L md (Language for Mental Image Description)'. This formal language has been already implemented on several versions of the intelligent system IMAGES including integrative multimedia understanding system IMAGES-M and conversation management system CMS. Dr. Yokota has authored numerous articles on AI and was the leader of many projects funded by Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT), and Fukuoka Institute of Technology (FIT).

« Un robot dans chaque foyer ». Voilà ce que prédit Bill Gates pour les années à venir ! Mais au fait, d'où viennent ces robots qui s'invitent chaque jour un peu plus dans notre vie quotidienne ? Tâches domestiques, transports, loisirs, soins... lesquels en font déjà partie intégrante ? Sont-ils plus performants que les humains ? Emploi, sécurité, relations humaines... : peuvent-ils s'avérer dangereux ? Et à l'avenir, jusqu'où iront-ils ? Autant de questions auxquelles cet ouvrage apporte des réponses, basées sur des entretiens avec des roboticiens et informaticiens reconnus.

Designing Autonomous Mobile Robots introduces the reader to the fundamental concepts of this complex field. The author addresses all the pertinent topics of the electronic hardware and software of mobile robot design, with particular emphasis on the more difficult problems of control, navigation, and sensor interfacing. Covering topics such as advanced sensor fusion, control systems for a wide array of application sensors and instrumentation, and fuzzy logic applications, this volume is essential reading for engineers undertaking robotics projects as well as undergraduate and graduate students studying robotic engineering, artificial intelligence, and cognitive science. Its state-of-the-art treatment of core concepts in mobile robotics helps and challenges readers in exploring new avenues in an exciting field. The accompanying CD-ROM provides software routines for the examples cited as well as an electronic version of the text. *Authored by a well-know pioneer of mobile robotics*Learn how to approach the design of and complex control system with confidence

An exploration of embodied intelligence and its implications points toward a theory of intelligence in general; with case studies of intelligent systems in ubiquitous computing, business and management, human memory, and robotics.