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Titlebook: Autonomous Military Robotics; Vishnu Nath,Stephen E. Levinson Book 2014 The Author(s) 2014 Computer vision.Deep learning.Defense robots.Ki

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發(fā)表于 2025-3-21 16:06:57 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Autonomous Military Robotics
影響因子2023Vishnu Nath,Stephen E. Levinson
視頻videohttp://file.papertrans.cn/167/166782/166782.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類SpringerBriefs in Computer Science
圖書封面Titlebook: Autonomous Military Robotics;  Vishnu Nath,Stephen E. Levinson Book 2014 The Author(s) 2014 Computer vision.Deep learning.Defense robots.Ki
影響因子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.
Pindex Book 2014
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發(fā)表于 2025-3-21 20:33:44 | 只看該作者
Bullet Kinematics,h to get an accurate shot. In the experimental setup we created, we did not attempt to snipe people at long range! On the contrary, we used commercially available a NERF? gun and NERF? bullets to simulate the firing of the gun and the motion of the bullet. The analysis that is presented in this chapter is for the NERF? gun and bullet only.
板凳
發(fā)表于 2025-3-22 01:30:45 | 只看該作者
地板
發(fā)表于 2025-3-22 05:04:04 | 只看該作者
Machine Learning,’. There is no probabilistic algorithm that will always return the optimum result with a probability of 1. That would make it a deterministic algorithm which, as has just been discussed, cannot handle every potential case. In this chapter, we discuss the algorithms that were employed to successfully complete the experiment.
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發(fā)表于 2025-3-22 09:25:41 | 只看該作者
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發(fā)表于 2025-3-22 19:55:18 | 只看該作者
Bilel Derbel,Mohamed Mosbah,Stefan Grunererform better on more capable hardware. In this chapter, we provide an introduction to the physical characteristics of the iCub robot platform that was used to perform the experiments and benchmark it using parameters that are relevant to the domain of robotics.
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發(fā)表于 2025-3-22 22:03:57 | 只看該作者
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發(fā)表于 2025-3-23 02:13:22 | 只看該作者
Introduction,attle can easily start in tropical jungles, move towards an urban attack on a city and might end with an ICBM attack from space. While definitely a frightening scenario, the truth is that battle lines no longer exist and conflicts may erupt at any place and time.
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發(fā)表于 2025-3-23 09:33:33 | 只看該作者
Robot Kinematics,erform better on more capable hardware. In this chapter, we provide an introduction to the physical characteristics of the iCub robot platform that was used to perform the experiments and benchmark it using parameters that are relevant to the domain of robotics.
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