Cognitive Robotics

Cognitive Robotics
Author: Angelo Cangelosi
Publisher: MIT Press
Total Pages: 497
Release: 2022-05-17
Genre: Technology & Engineering
ISBN: 0262046830
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The current state of the art in cognitive robotics, covering the challenges of building AI-powered intelligent robots inspired by natural cognitive systems. A novel approach to building AI-powered intelligent robots takes inspiration from the way natural cognitive systems—in humans, animals, and biological systems—develop intelligence by exploiting the full power of interactions between body and brain, the physical and social environment in which they live, and phylogenetic, developmental, and learning dynamics. This volume reports on the current state of the art in cognitive robotics, offering the first comprehensive coverage of building robots inspired by natural cognitive systems. Contributors first provide a systematic definition of cognitive robotics and a history of developments in the field. They describe in detail five main approaches: developmental, neuro, evolutionary, swarm, and soft robotics. They go on to consider methodologies and concepts, treating topics that include commonly used cognitive robotics platforms and robot simulators, biomimetic skin as an example of a hardware-based approach, machine-learning methods, and cognitive architecture. Finally, they cover the behavioral and cognitive capabilities of a variety of models, experiments, and applications, looking at issues that range from intrinsic motivation and perception to robot consciousness. Cognitive Robotics is aimed at an interdisciplinary audience, balancing technical details and examples for the computational reader with theoretical and experimental findings for the empirical scientist.

Cognitive Computing for Human-Robot Interaction

Cognitive Computing for Human-Robot Interaction
Author: Mamta Mittal
Publisher: Academic Press
Total Pages: 420
Release: 2021-08-13
Genre: Computers
ISBN: 0323856470
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Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: - Introduces several new contributions to the representation and management of humans in autonomous robotic systems; - Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; - Engages with the potential repercussions of cognitive computing and HRI in the real world. - Introduces several new contributions to the representation and management of humans in an autonomous robotic system - Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society - Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario

Cognitive Robotics & Control

Cognitive Robotics & Control
Author: Cecilio Angulo
Publisher: MDPI
Total Pages: 170
Release: 2020-06-16
Genre: Technology & Engineering
ISBN: 3039362461
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Robotics and control are both research and application domains that have been frequently engineered through the use of interdisciplinary approaches like cybernetics. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, and is concerned with knowledge acquisition and understanding through thought, experience, and the senses. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures that enable systems to behave in an autonomous way. The main aim of this book is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures, and implementations for reasoning, problem solving, or decision making are considered in the domain of robotics and control.

Robot Cognition and Navigation

Robot Cognition and Navigation
Author: Srikanta Patnaik
Publisher: Springer Science & Business Media
Total Pages: 296
Release: 2007-07-12
Genre: Technology & Engineering
ISBN: 3540689168
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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.

Deep Learning for Robot Perception and Cognition

Deep Learning for Robot Perception and Cognition
Author: Alexandros Iosifidis
Publisher: Academic Press
Total Pages: 638
Release: 2022-02-04
Genre: Technology & Engineering
ISBN: 0323885721
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Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis

Digital Transformation

Digital Transformation
Author: Reimund Neugebauer
Publisher: Springer
Total Pages: 393
Release: 2019-05-14
Genre: Technology & Engineering
ISBN: 3662581345
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With the exception of written letters and personal conversations, digital technology forms the basis of nearly every means of communication and information that we use today. It is also used to control the essential elements of economic, scientific, and public and private life: security, production, mobility, media, and healthcare. Without exaggerating it is possible to say that digital technology has become one of the foundations of our technologically oriented civilization. The benefits of modern data technology are so impressive and the potential for future applications so enormous that we cannot fail to promote its development if we are to retain our leading role in the competitive international marketplace. In this process, security plays a vital role in each of the areas of application of digital technology — the more technological sectors are entrusted to data systems technology, the more important their reliability becomes to us. Developing digital systems further while simultaneously ensuring that they always act and respond in the best interests of people is a central goal of the technological research and development propagated and conducted by Fraunhofer.

Intelligent Control of Robotic Systems

Intelligent Control of Robotic Systems
Author: D. Katic
Publisher: Springer Science & Business Media
Total Pages: 308
Release: 2013-03-14
Genre: Technology & Engineering
ISBN: 9401703175
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As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems.

Innovations in Applied Artificial Intelligence

Innovations in Applied Artificial Intelligence
Author: Bob Orchard
Publisher: Springer
Total Pages: 1293
Release: 2004-04-22
Genre: Computers
ISBN: 3540246770
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“Intelligent systems must perform in order to be in demand. ” Intelligent systems technology is being applied steadily in solving many day-to-day problems. Each year the list of real-world deployed applications that inconspicuously host the results of research in the area grows considerably. These applications are having a significant impact in industrial operations, in financial circles, in transportation, in education, in medicine, in consumer products, in games and elsewhere. A set of selected papers presented at the seventeenth in the series of conferences on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2004), sponsored by the International Society of Applied Intelligence, is offered in this manuscript. These papers highlight novel applications of the technology and show how new research could lead to new and innovative applications. We hope that you find these papers to be educational, useful in your own research, and stimulating. In addition, we have introduced some special sessions to emphasize a few areas of artificial intelligence (AI) that are either relatively new, have received considerable attention recently or perhaps have not yet been represented well. To this end, we have included special sessions on e-learning, bioinformatics, and human-robot interaction (HRI) to complement the usual offerings in areas such as data mining, machine learning, intelligent systems, neural networks, genetic algorithms, autonomous agents, natural language processing, intelligent user interfaces, evolutionary computing, fuzzy logic, computer vision and image processing, reasoning, heuristic search, security, Internet applications, constraint satisfaction problems, design, and expert systems.

The Soar Cognitive Architecture

The Soar Cognitive Architecture
Author: John E. Laird
Publisher: MIT Press
Total Pages: 391
Release: 2019-08-20
Genre: Computers
ISBN: 0262538539
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The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.

Interactive Task Learning

Interactive Task Learning
Author: Kevin A. Gluck
Publisher: MIT Press
Total Pages: 355
Release: 2019-08-16
Genre: Computers
ISBN: 0262349434
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Experts from a range of disciplines explore how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. Humans are not limited to a fixed set of innate or preprogrammed tasks. We learn quickly through language and other forms of natural interaction, and we improve our performance and teach others what we have learned. Understanding the mechanisms that underlie the acquisition of new tasks through natural interaction is an ongoing challenge. Advances in artificial intelligence, cognitive science, and robotics are leading us to future systems with human-like capabilities. A huge gap exists, however, between the highly specialized niche capabilities of current machine learning systems and the generality, flexibility, and in situ robustness of human instruction and learning. Drawing on expertise from multiple disciplines, this Strüngmann Forum Report explores how humans and artificial agents can quickly learn completely new tasks through natural interactions with each other. The contributors consider functional knowledge requirements, the ontology of interactive task learning, and the representation of task knowledge at multiple levels of abstraction. They explore natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex, dynamic environments. They discuss research challenges and opportunities, including ethical considerations, and make proposals to further understanding of interactive task learning and create new capabilities in assistive robotics, healthcare, education, training, and gaming. Contributors Tony Belpaeme, Katrien Beuls, Maya Cakmak, Joyce Y. Chai, Franklin Chang, Ropafadzo Denga, Marc Destefano, Mark d'Inverno, Kenneth D. Forbus, Simon Garrod, Kevin A. Gluck, Wayne D. Gray, James Kirk, Kenneth R. Koedinger, Parisa Kordjamshidi, John E. Laird, Christian Lebiere, Stephen C. Levinson, Elena Lieven, John K. Lindstedt, Aaron Mininger, Tom Mitchell, Shiwali Mohan, Ana Paiva, Katerina Pastra, Peter Pirolli, Roussell Rahman, Charles Rich, Katharina J. Rohlfing, Paul S. Rosenbloom, Nele Russwinkel, Dario D. Salvucci, Matthew-Donald D. Sangster, Matthias Scheutz, Julie A. Shah, Candace L. Sidner, Catherine Sibert, Michael Spranger, Luc Steels, Suzanne Stevenson, Terrence C. Stewart, Arthur Still, Andrea Stocco, Niels Taatgen, Andrea L. Thomaz, J. Gregory Trafton, Han L. J. van der Maas, Paul Van Eecke, Kurt VanLehn, Anna-Lisa Vollmer, Janet Wiles, Robert E. Wray III, Matthew Yee-King