Autonomous Military Robotics (Paperback, 2014)

This SpringerBrief reveals the latest techniques in computer vision and machine learning on robots that are designed as accurate and efficient military snipers. Militaries around the world are investigating this technology to simplify the time, cost and safety measures necessary for training human snipers. These robots are developed by combining crucial aspects of computer science research areas including image processing, robotic kinematics and learning algorithms. The authors explain how a new humanoid robot, the iCub, uses high-speed cameras and computer vision algorithms to track the object that has been classified as a target. The robot adjusts its arm and the gun muzzle for maximum accuracy, due to a neural model that includes the parameters of its joint angles, the velocity of the bullet and the approximate distance of the target. A thorough literature review provides helpful context for the experiments. Of practical interest to military forces around the world, this brief is designed for professionals and researchers working in military robotics. It will also be useful for advanced level computer science students focused on computer vision, AI and machine learning issues.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	April 2014
First published:	2014
Authors:	Vishnu Nath • Stephen E Levinson
Dimensions:	235 x 155 x 4mm (L x W x T)
Format:	Paperback
Pages:	56
Edition:	2014
ISBN-13:	978-3-319-05605-0
Categories:	Books > Social sciences > Warfare & defence > Weapons & equipment > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
LSN:	3-319-05605-0
Barcode:	9783319056050

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