標(biāo)題: Titlebook: Creating Autonomous Vehicle Systems, Second Edition; Shaoshan Liu,Liyun Li,Jean-Luc Gaudiot Book 2020Latest edition Springer Nature Switze [打印本頁] 作者: 祈求 時(shí)間: 2025-3-21 16:33
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書目名稱Creating Autonomous Vehicle Systems, Second Edition網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Creating Autonomous Vehicle Systems, Second Edition被引頻次
書目名稱Creating Autonomous Vehicle Systems, Second Edition被引頻次學(xué)科排名
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書目名稱Creating Autonomous Vehicle Systems, Second Edition年度引用學(xué)科排名
書目名稱Creating Autonomous Vehicle Systems, Second Edition讀者反饋
書目名稱Creating Autonomous Vehicle Systems, Second Edition讀者反饋學(xué)科排名
作者: 聽覺 時(shí)間: 2025-3-21 21:39 作者: 深陷 時(shí)間: 2025-3-22 04:04 作者: dendrites 時(shí)間: 2025-3-22 07:19
Water Politics and Development Cooperationd on lane segmentation of the HD-maps. Routing simply informs the autonomous vehicle how to reach its destination by following a sequence of lanes on the HD-maps. Its output is also sent to the downstream planning and control modules.作者: 方舟 時(shí)間: 2025-3-22 12:30 作者: debouch 時(shí)間: 2025-3-22 14:06
Perception in Autonomous Driving,trol depend on a correct perception output, its importance cannot be overstated. In this chapter, major functionalities of perception are covered, along with public datasets, problem definitions, and typical algorithms. Algorithms based on neural networks are discussed in the next chapter.作者: debouch 時(shí)間: 2025-3-22 20:14
Prediction and Routing,d on lane segmentation of the HD-maps. Routing simply informs the autonomous vehicle how to reach its destination by following a sequence of lanes on the HD-maps. Its output is also sent to the downstream planning and control modules.作者: Antecedent 時(shí)間: 2025-3-22 23:27 作者: flamboyant 時(shí)間: 2025-3-23 01:39
Book 2020Latest editionheir practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud 作者: nerve-sparing 時(shí)間: 2025-3-23 09:27
https://doi.org/10.1007/978-3-540-76711-4 planning and control problems. We thus conclude that reinforcement learning-based planning and control will gradually become a viable solution to autonomous driving planning and control problems or at least become a necessary complement to current optimization approaches.作者: burnish 時(shí)間: 2025-3-23 11:27 作者: 缺陷 時(shí)間: 2025-3-23 17:46 作者: 營養(yǎng) 時(shí)間: 2025-3-23 19:10
https://doi.org/10.1007/978-3-540-76707-7ject detection, semantic segmentation, etc. Most state-of-the-art algorithms now apply one type of neural network that is based on convolution operation, and the field is rapidly progressing. In this chapter, we will cover selected deep-learning-based algorithms for perception in autonomous driving.作者: 直覺沒有 時(shí)間: 2025-3-23 23:42 作者: Meander 時(shí)間: 2025-3-24 05:12 作者: IVORY 時(shí)間: 2025-3-24 08:40
Perception in Autonomous Driving,sensory data. In order for autonomous driving vehicles to be safe and intelligent, perception modules must be able to detect any obstacle, to recognize road surface, lane dividers, traffic signs and lights, to track moving objects in 3D, etc. Since all subsequent driving decisions, planning, and con作者: 吞下 時(shí)間: 2025-3-24 12:15 作者: cravat 時(shí)間: 2025-3-24 15:52 作者: lesion 時(shí)間: 2025-3-24 21:43
Decision, Planning, and Control, feedback .. Decision, planning, and control are the modules that compute how the autonomous vehicle should maneuver. These modules constitute the traditional narrow concept of planning and control. While they all solve the same problem of how the autonomous vehicle should behave, they operate at di作者: 容易做 時(shí)間: 2025-3-25 02:08
Reinforcement Learning-Based Planning and Control,me increasingly popular with recent developments in artificial intelligence. Even though current state-of-the-art learning-based approaches to planning and control have their limitations, we feel they will become extremely important in the future and that, as technical trends, they should not be ove作者: Consensus 時(shí)間: 2025-3-25 03:38 作者: 好忠告人 時(shí)間: 2025-3-25 10:15
Cloud Platform for Autonomous Driving,ation tests for new algorithm deployment, offline deep learning model training, HD map generation, etc. These services require infrastructure support including distributed computing, distributed storage, as well as heterogeneous computing. In this chapter, we present the details of our implementatio作者: expeditious 時(shí)間: 2025-3-25 15:22
Water Politics and Development Cooperations chapter we first study different localization techniques, including GNSS, LiDAR and High-Definition Maps, Visual Odometry, and other Dead Reckoning sensors. We also look into several real-world examples of applying sensor fusion techniques to combine multiple sensors to provide more accurate local作者: 多樣 時(shí)間: 2025-3-25 17:38 作者: Sad570 時(shí)間: 2025-3-25 21:05
https://doi.org/10.1007/978-3-540-76707-7p learning, has greatly changed the field of computer vision, making significant progress in solving various problems such as image classification, object detection, semantic segmentation, etc. Most state-of-the-art algorithms now apply one type of neural network that is based on convolution operati作者: exceed 時(shí)間: 2025-3-26 00:26 作者: 我的巨大 時(shí)間: 2025-3-26 06:52
Ursula M. Staudinger,Heinz H?fner feedback .. Decision, planning, and control are the modules that compute how the autonomous vehicle should maneuver. These modules constitute the traditional narrow concept of planning and control. While they all solve the same problem of how the autonomous vehicle should behave, they operate at di作者: HATCH 時(shí)間: 2025-3-26 12:22 作者: 清洗 時(shí)間: 2025-3-26 14:21
https://doi.org/10.1007/978-3-540-76707-7em is a very complex software and hardware system. In order to coordinate the interactions between different components, an operating system is required, and the operating system we discuss in this chapter is based on the Robot Operating System (ROS). Next we discuss the computing platform, which is作者: 移動(dòng) 時(shí)間: 2025-3-26 18:43 作者: dysphagia 時(shí)間: 2025-3-26 23:35 作者: inchoate 時(shí)間: 2025-3-27 04:58 作者: Apraxia 時(shí)間: 2025-3-27 05:50 作者: Factual 時(shí)間: 2025-3-27 09:44 作者: 用手捏 時(shí)間: 2025-3-27 14:12 作者: conquer 時(shí)間: 2025-3-27 21:44
Ursula M. Staudinger,Heinz H?fner feedback .. Decision, planning, and control are the modules that compute how the autonomous vehicle should maneuver. These modules constitute the traditional narrow concept of planning and control. While they all solve the same problem of how the autonomous vehicle should behave, they operate at different levels of the problem abstraction.作者: 招待 時(shí)間: 2025-3-28 01:38 作者: 行業(yè) 時(shí)間: 2025-3-28 03:15
Autonomous Vehicle Localization,s chapter we first study different localization techniques, including GNSS, LiDAR and High-Definition Maps, Visual Odometry, and other Dead Reckoning sensors. We also look into several real-world examples of applying sensor fusion techniques to combine multiple sensors to provide more accurate localization.作者: 散開 時(shí)間: 2025-3-28 06:19
Decision, Planning, and Control, feedback .. Decision, planning, and control are the modules that compute how the autonomous vehicle should maneuver. These modules constitute the traditional narrow concept of planning and control. While they all solve the same problem of how the autonomous vehicle should behave, they operate at different levels of the problem abstraction.作者: 使困惑 時(shí)間: 2025-3-28 12:58 作者: 有幫助 時(shí)間: 2025-3-28 17:08
Book 2020Latest editionvehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map—in addition to training better recognition, tracking, and decision models..Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the aut作者: flamboyant 時(shí)間: 2025-3-28 21:22 作者: idiopathic 時(shí)間: 2025-3-29 02:22
Creating Autonomous Vehicle Systems, Second Edition
