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.
Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester, UK, and coauthor of Developmental Robotics (MIT Press).
Minoru Asada is Vice-President of International Professional University of Technology in Osaka, and Specially Appointed Professor in the Institute for Open and Transdisciplinary Research Initiatives at Osaka University.
“A comprehensive, contemporary overview of the field of cognitive robotics, an approach to understanding intelligence ripe for explosive growth. Both biological and artificial intelligence researchers will benefit from it!”
Jay McClelland, Director, Center for Mind, Brain, Computation and Technology, Stanford University
The open access edition of this book was made possible by generous funding and support from MIT Press Direct to Open