Central Library

Normal view MARC view ISBD view

Autonomous Military Robotics [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, 56 p. 18 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319056067.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 -- Bullet Kinematics -- Experimental Results -- Future Direction.
In: Springer eBooksSummary: 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.
    average rating: 0.0 (0 votes)
No physical items for this record

Introduction -- Overview of Probability and Statistics -- Primer on Matrices and Determinants -- Robot Kinematics -- Computer Vision -- Machine Learning -- Bullet Kinematics -- Experimental Results -- Future Direction.

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.

There are no comments for this item.

Log in to your account to post a comment.