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Autonomous Robotics and Deep Learning [electronic resource] / by Vishnu Nath, Stephen E. Levinson.

By: Nath, Vishnu [author.].
Contributor(s): Levinson, Stephen E [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Computer Science: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: VIII, 66 p. 57 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319056036.Subject(s): Computer science | User interfaces (Computer systems) | Artificial intelligence | Computer graphics | Image processing | Computer Science | Artificial Intelligence (incl. Robotics) | Image Processing and Computer Vision | User Interfaces and Human Computer Interaction | Computer Imaging, Vision, Pattern Recognition and GraphicsAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Introduction -- Overview of Probability and Statistics -- Primer on Matrices and Determinants -- Robot Kinematics -- Computer Vision -- Machine Learning -- Experimental Results -- Future Direction.
In: Springer eBooksSummary: This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop "true consciousness." It illustrates the critical first step towards reaching "deep learning," long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning.
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Introduction -- Overview of Probability and Statistics -- Primer on Matrices and Determinants -- Robot Kinematics -- Computer Vision -- Machine Learning -- Experimental Results -- Future Direction.

This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop "true consciousness." It illustrates the critical first step towards reaching "deep learning," long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning.

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