Cognitive robotics
Contributor(s): Cangelosi, Angelo [ed.] | Asada, Minoru [ed.].
Series: Intelligent robotics and autonomous agents. edited by / Ronald C. Arkin.Publisher: Cambridge MIT Press 2022Description: xi, 481p.ISBN: 9780262046831.Subject(s): Autonomous robots | AI-powered intelligent robotsDDC classification: 629.892 | C659 Summary: The current state of the art in cognitive robotics covers 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.Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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PK Kelkar Library, IIT Kanpur | General Stacks | 629.892 C659 (Browse shelf) | Available | A186359 |
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: General Stacks Close shelf browser
629.892 C421a Autonomous intelligent vehicles | 629.892 C424ME MANIPULATION ROBOTS | 629.892 C556B BUILDING ROBOT DRIVE TRAINS | 629.892 C659 Cognitive robotics | 629.892 C813r Robotics, vision and control | 629.892 C844i2 cop.2 Introduction to robotics | 629.892 C844i2 cop.4 Introduction to robotics |
The current state of the art in cognitive robotics covers 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.
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