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Titlebook: Intelligent Autonomous Drones with Cognitive Deep Learning; Build AI-Enabled Lan David Allen Blubaugh,Steven D. Harbour,Michael J. Book 20

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發(fā)表于 2025-3-21 19:54:39 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Intelligent Autonomous Drones with Cognitive Deep Learning
副標題Build AI-Enabled Lan
編輯David Allen Blubaugh,Steven D. Harbour,Michael J.
視頻videohttp://file.papertrans.cn/470/469371/469371.mp4
概述Develop your own AI enabled drone, understanding the software and hardware requirements.Model the behavior of the designed AI-drone within multiple simulation environments such as VREP, Gazebo,‘and Ai
圖書封面Titlebook: Intelligent Autonomous Drones with Cognitive Deep Learning; Build AI-Enabled Lan David Allen Blubaugh,Steven D. Harbour,Michael J. Book 20
描述What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone..You‘ll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems.?.Using this approach you‘ll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you‘ll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability..Intelligent Autonomous Drones wi
出版日期Book 2022
關鍵詞Sensors; Inertial Measurement Unit; IMU; Sense Detect and Avoid; SDaA; Insurance considerations for an AI
版次1
doihttps://doi.org/10.1007/978-1-4842-6803-2
isbn_softcover978-1-4842-6802-5
isbn_ebook978-1-4842-6803-2
copyrightDavid Allen Blubaugh, Steven D. Harbour, Benjamin Sears, Michael J. Findler 2022
The information of publication is updating

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發(fā)表于 2025-3-21 23:20:18 | 只看該作者
Book 2022swer these questions and more, and empower you to develop your own AI-enabled drone..You‘ll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards establ
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發(fā)表于 2025-3-22 00:50:44 | 只看該作者
AI Rover System Design and Analysis,e simplifications of complex ideas. For example, Newton’s Second Law of Motion tries to explain the physics of momentum. It is a great approximation, but it is not 100% accurate. It leaves out gravity, friction, and so on. But it . helpful.
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Reinforced Learning,gaming module that works as a flight simulator, a computer vision system that detects the pilot’s gestures, a flight dynamics analyzer for verifying the safety limits of the state space variables during a simulated flight, and a module to calculate the Q-function and the learned policy.
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Adding Sensors to Our Simulation,R, radar, cameras, etc. Our LiDAR sensor develops the first distance-ranging capabilities of the rover. We will develop Python scripts that directly control the rover’s wheels through the differential drive plug-in. Finally, we will experiment with a keyboard control (Teleops) of the rover via a Python script.
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