NDLI: Autonomous Military Robotics

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Autonomous Military Robotics

Content Provider	Springer-eBooks
Author	Nath, Vishnu Levinson, Stephen E.
Copyright Year	2014
Abstract	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.
File Format	PDF
ISBN	9783319056067
Language	English
Publisher	SpringerLink Springer eBooks
Access Restriction	Subscribed
Subject Keyword	Computer Science Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Book

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