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Motion Planning For Autonomous Vehicles In Partially Observable Environments


Motion Planning For Autonomous Vehicles In Partially Observable Environments
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Motion Planning For Autonomous Vehicles In Partially Observable Environments


Motion Planning For Autonomous Vehicles In Partially Observable Environments
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Author : Taş, Ömer Şahin
language : en
Publisher: KIT Scientific Publishing
Release Date : 2023-10-23

Motion Planning For Autonomous Vehicles In Partially Observable Environments written by Taş, Ömer Şahin and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-23 with categories.


This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.



Deep Learning For Unmanned Systems


Deep Learning For Unmanned Systems
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Author : Anis Koubaa
language : en
Publisher: Springer Nature
Release Date : 2021-10-01

Deep Learning For Unmanned Systems written by Anis Koubaa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Technology & Engineering categories.


This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.



On Road Intelligent Vehicles


On Road Intelligent Vehicles
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Author : Rahul Kala
language : en
Publisher: Butterworth-Heinemann
Release Date : 2016-04-27

On Road Intelligent Vehicles written by Rahul Kala and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-27 with Technology & Engineering categories.


On-Road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems deals with the technology of autonomous vehicles, with a special focus on the navigation and planning aspects, presenting the information in three parts. Part One deals with the use of different sensors to perceive the environment, thereafter mapping the multi-domain senses to make a map of the operational scenario, including topics such as proximity sensors which give distances to obstacles, vision cameras, and computer vision techniques that may be used to pre-process the image, extract relevant features, and use classification techniques like neural networks and support vector machines for the identification of roads, lanes, vehicles, obstacles, traffic lights, signs, and pedestrians. With a detailed insight into the technology behind the vehicle, Part Two of the book focuses on the problem of motion planning. Numerous planning techniques are discussed and adapted to work for multi-vehicle traffic scenarios, including the use of sampling based approaches comprised of Genetic Algorithm and Rapidly-exploring Random Trees and Graph search based approaches, including a hierarchical decomposition of the algorithm and heuristic selection of nodes for limited exploration, Reactive Planning based approaches, including Fuzzy based planning, Potential Field based planning, and Elastic Strip and logic based planning. Part Three of the book covers the macroscopic concepts related to Intelligent Transportation Systems with a discussion of various topics and concepts related to transportation systems, including a description of traffic flow, the basic theory behind transportation systems, and generation of shock waves. - Provides an overall coverage of autonomous vehicles and Intelligent Transportation Systems - Presents a detailed overview, followed by the challenging problems of navigation and planning - Teaches how to compare, contrast, and differentiate navigation algorithms



Sensing And Control For Autonomous Vehicles


Sensing And Control For Autonomous Vehicles
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Author : Thor I. Fossen
language : en
Publisher: Springer
Release Date : 2017-05-26

Sensing And Control For Autonomous Vehicles written by Thor I. Fossen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-26 with Technology & Engineering categories.


This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light intervention work, underwater survey and collection of oceanographic/biological data. Autonomous unmanned aerial systems can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and a minimum of intelligence. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles. Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data, for assimilation of climate and environmental models and to complement global satellite systems. The target audience primarily comprises research experts in the field of control theory, but the book may also be beneficial for graduate students.



Belief State Planning For Autonomous Driving Planning With Interaction Uncertain Prediction And Uncertain Perception


Belief State Planning For Autonomous Driving Planning With Interaction Uncertain Prediction And Uncertain Perception
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Author : Hubmann, Constantin
language : en
Publisher: KIT Scientific Publishing
Release Date : 2021-09-13

Belief State Planning For Autonomous Driving Planning With Interaction Uncertain Prediction And Uncertain Perception written by Hubmann, Constantin and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-13 with Technology & Engineering categories.


This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty.



Autonomous Driving Algorithms And Its Ic Design


Autonomous Driving Algorithms And Its Ic Design
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Author : Jianfeng Ren
language : en
Publisher: Springer Nature
Release Date : 2023-08-09

Autonomous Driving Algorithms And Its Ic Design written by Jianfeng Ren and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-09 with Technology & Engineering categories.


With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years. The implementation of autonomous driving requires new sources of sensory data, such as cameras, radars, and lidars, and the algorithm processing requires a high degree of parallel computing. In this regard, traditional CPUs have insufficient computing power, while DSPs are good at image processing but lack sufficient performance for deep learning. Although GPUs are good at training, they are too “power-hungry,” which can affect vehicle performance. Therefore, this book looks to the future, arguing that custom ASICs are bound to become mainstream. With the goal of ICs design for autonomous driving, this book discusses the theory and engineering practice of designing future-oriented autonomous driving SoC chips. The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 address the optimization of deep learning models and the design of deep learning chips, while Chapters 11-12 cover automatic driving software architecture design. Chapter 13 discusses the 5G application on autonomous drving. This book is suitable for all undergraduates, graduate students, and engineering technicians who are interested in autonomous driving.



Decision Making Strategies For Automated Driving In Urban Environments


Decision Making Strategies For Automated Driving In Urban Environments
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Author : Antonio Artuñedo
language : en
Publisher: Springer Nature
Release Date : 2020-04-25

Decision Making Strategies For Automated Driving In Urban Environments written by Antonio Artuñedo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-25 with Technology & Engineering categories.


This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.



Internet Of Vehicles And Its Applications In Autonomous Driving


Internet Of Vehicles And Its Applications In Autonomous Driving
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Author : Nishu Gupta
language : en
Publisher: Springer Nature
Release Date : 2020-09-18

Internet Of Vehicles And Its Applications In Autonomous Driving written by Nishu Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-18 with Technology & Engineering categories.


This book provides an insight on the importance that Internet of Vehicles (IoV) solutions can have in taking care of vehicular safety through internetworking and automation. Key features of the book are the inclusion and elaboration of recent and emerging developments in various specializations of intelligent transportation systems and their solutions by incorporating IoT (Internet of Things) and IoV. This book presents to its readers useful IoV applications and architectures that cater to their improved driving requirements and lead towards autonomous driving. The application domains have a large range in which vehicular networking, communication technology, sensor devices, computing materials and devices, IoT communication, vehicular and on-road safety, data security and other topics are included.



The Darpa Urban Challenge


The Darpa Urban Challenge
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Author : Martin Buehler
language : en
Publisher: Springer
Release Date : 2009-11-26

The Darpa Urban Challenge written by Martin Buehler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-26 with Technology & Engineering categories.


By the dawn of the new millennium, robotics has undergone a major transformation in scope and dimensions. This expansion has been brought about by the maturity of the field and the advances in its related technologies. From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and communities, providing support in services, entertainment, education, healthcare, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across diverse research areas and scientific disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the field of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on the basis of their significance and quality. It is our hope that the wider dissemination of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing field.



Probabilistic Mapping Of Spatial Motion Patterns For Mobile Robots


Probabilistic Mapping Of Spatial Motion Patterns For Mobile Robots
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Author : Tomasz Piotr Kucner
language : en
Publisher: Springer Nature
Release Date : 2020-03-28

Probabilistic Mapping Of Spatial Motion Patterns For Mobile Robots written by Tomasz Piotr Kucner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Technology & Engineering categories.


This book describes how robots can make sense of motion in their surroundings and use the patterns they observe to blend in better in dynamic environments shared with humans.The world around us is constantly changing. Nonetheless, we can find our way and aren’t overwhelmed by all the buzz, since motion often follows discernible patterns. Just like humans, robots need to understand the patterns behind the dynamics in their surroundings to be able to efficiently operate e.g. in a busy airport. Yet robotic mapping has traditionally been based on the static world assumption, which disregards motion altogether. In this book, the authors describe how robots can instead explicitly learn patterns of dynamic change from observations, store those patterns in Maps of Dynamics (MoDs), and use MoDs to plan less intrusive, safer and more efficient paths. The authors discuss the pros and cons of recently introduced MoDs and approaches to MoD-informed motion planning, and provide an outlook on future work in this emerging, fascinating field.