Download or read book Human like Motion Planning for Autonomous Ground Vehicle Applications written by Maradona Rodrigues and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Autonomous Ground Vehicles written by Ümit Özgüner and published by Artech House. This book was released on 2011 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles.Covering sensors, estimation, and sensor fusion to percept the vehicle motion and surrounding objects, this unique book explains the key aspects that makes autonomous vehicle behavior possible. Moreover, you find detailed examples of fusion and Kalman filtering. From maps, path planning, and obstacle avoidance scenarios...to cooperative mobility among autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication, this forward-looking book presents the most critical topics in the field today.

Download or read book Intelligent Unmanned Ground Vehicles written by Martial H. Hebert and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Unmanned Ground Vehicles describes the technology developed and the results obtained by the Carnegie Mellon Robotics Institute in the course of the DARPA Unmanned Ground Vehicle (UGV) project. The goal of this work was to equip off-road vehicles with computer-controlled, unmanned driving capabilities. The book describes contributions in the area of mobility for UGVs including: tools for assembling complex autonomous mobility systems; on-road and off-road navigation; sensing techniques; and route planning algorithms. In addition to basic mobility technology, the book covers a number of integrated systems demonstrated in the field in realistic scenarios. The approaches presented in this book can be applied to a wide range of mobile robotics applications, from automated passenger cars to planetary exploration, and construction and agricultural machines. Intelligent Unmanned Ground Vehicles shows the progress that was achieved during this program, from brittle specially-built robots operating under highly constrained conditions, to groups of modified commercial vehicles operating in tough environments. One measure of progress is how much of this technology is being used in other applications. For example, much of the work in road-following, architectures and obstacle detection has been the basis for the Automated Highway Systems (AHS) prototypes currently under development. AHS will lead to commercial prototypes within a few years. The cross-country technology is also being used in the development of planetary rovers with a projected launch date within a few years. The architectural tools built under this program have been used in numerous applications, from an automated harvester to an autonomous excavator. The results reported in this work provide tools for further research development leading to practical, reliable and economical mobile robots.

Download or read book Safe Interactive Motion Planning for Autonomous Cars written by Mingyu Wang and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade, the autonomous driving industry has seen tremendous advancements thanks to the progress in computation, artificial intelligence, sensing capabilities, and other technologies related to autonomous vehicles. Today, autonomous cars operate in dense urban traffic, compared to the last generation of robots that were confined to isolated workspaces. In these human-populated environments, autonomous cars need to understand their surroundings and behave in an interpretable, human-like manner. In addition, autonomous robots are engaged in more social interactions with other humans, which requires an understanding of how multiple reactive agents act. For example, during lane changes, most attentive drivers would slow down to give space if an adjacent car shows signs of executing a lane change. For an autonomous car, understanding the mutual dependence between its action and others' actions is essential for the safety and viability of the autonomous driving industry. However, most existing trajectory planning approaches ignore the coupling between all agents' behaviors and treat the decisions of other agents as immutable. As a result, the planned trajectories are conservative, less intuitive, and may lead to unsafe behaviors. To address these challenges, we present motion planning frameworks that maintain the coupling of prediction and planning by explicitly modeling their mutual dependency. In the first part, we examine reciprocal collision avoidance behaviors among a group of intelligent robots. We propose a distributed, real-time collision avoidance algorithm based on Voronoi diagrams that only requires relative position measurements from onboard sensors. When necessary, the proposed controller minimally modifies a nominal control input and provides collision avoidance behaviors even with noisy sensor measurements. In the second part, we introduce a nonlinear receding horizon game-theoretic planner that approximates a Nash equilibrium in competitive scenarios among multiple cars. The proposed planner uses a sensitivity-enhanced objective function and iteratively plans for the ego vehicle and the other vehicles to reach an equilibrium strategy. The resulting trajectories show that the ego vehicle can leverage its influence on other vehicles' decisions and intentionally change their courses. The resulting trajectories exhibit rich interactive behaviors, such as blocking and overtaking in competitive scenarios among multiple cars. In the last part, we propose a risk-aware game-theoretic planner that takes into account uncertainties of the future trajectories. We propose an iterative dynamic programming algorithm to solve a feedback equilibrium strategy set for interacting agents with different risk sensitivities. Through simulations, we show that risk-aware planners generate safer behaviors when facing uncertainties in safety-critical situations. We also present a solution for the "inverse" risk-sensitive planning algorithm. The goal of the inverse problem is to learn the cost function as well as risk sensitivity for each individual. The proposed algorithm learns the cost function parameters from datasets collected from demonstrations with various risk sensitivity. Using the learned cost function, the ego vehicle can estimate the risk profile of an interacting agent online to improve safety and efficiency.

Download or read book Technology Development for Army Unmanned Ground Vehicles written by National Research Council and published by National Academies Press. This book was released on 2003-02-01 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned ground vehicles (UGV) are expected to play a key role in the Army's Objective Force structure. These UGVs would be used for weapons platforms, logistics carriers, and reconnaissance, surveillance, and target acquisition among other things. To examine aspects of the Army's UGV program, assess technology readiness, and identify key issues in implementing UGV systems, among other questions, the Deputy Assistant Secretary of the Army for Research and Technology asked the National Research Council (NRC) to conduct a study of UGV technologies. This report discusses UGV operational requirements, current development efforts, and technology integration and roadmaps to the future. Key recommendations are presented addressing technical content, time lines, and milestones for the UGV efforts.

Download or read book Motion planning and feedback control techniques with applications to long tractor trailer vehicles written by Oskar Ljungqvist and published by Linköping University Electronic Press. This book was released on 2020-04-20 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. At the same time, there has been a growing demand within the transportation sector to increase efficiency and to reduce the environmental impact related to transportation of people and goods. Therefore, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems and self-driving vehicles. Autonomous vehicles are expected to have their first big impact in closed environments, such as mines, harbors, loading and offloading sites. In such areas, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites, tractor-trailer vehicles are frequently used for transportation. These vehicles are composed of several interconnected vehicle segments, and are therefore large, complex and unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control techniques for such systems. The contributions of this thesis are within the area of motion planning and feedback control for long tractor-trailer combinations operating at low-speeds in closed and unstructured environments. It includes development of motion planning and feedback control frameworks, structured design tools for guaranteeing closed-loop stability and experimental validation of the proposed solutions through simulations, lab and field experiments. Even though the primary application in this work is tractor-trailer vehicles, many of the proposed approaches can with some adjustments also be used for other systems, such as drones and ships. The developed sampling-based motion planning algorithms are based upon the probabilistic closed-loop rapidly exploring random tree (CL-RRT) algorithm and the deterministic lattice-based motion planning algorithm. It is also proposed to use numerical optimal control offline for precomputing libraries of optimized maneuvers as well as during online planning in the form of a warm-started optimization step. To follow the motion plan, several predictive path-following control approaches are proposed with different computational complexity and performance. Common for these approaches are that they use a path-following error model of the vehicle for future predictions and are tailored to operate in series with a motion planner that computes feasible paths. The design strategies for the path-following approaches include linear quadratic (LQ) control and several advanced model predictive control (MPC) techniques to account for physical and sensing limitations. To strengthen the practical value of the developed techniques, several of the proposed approaches have been implemented and successfully demonstrated in field experiments on a full-scale test platform. To estimate the vehicle states needed for control, a novel nonlinear observer is evaluated on the full-scale test vehicle. It is designed to only utilize information from sensors that are mounted on the tractor, making the system independent of any sensor mounted on the trailer. Under de senaste årtiondena har utvecklingen av sensor- och hårdvaruteknik gått i en snabb takt, samtidigt som nya metoder och algoritmer har introducerats. Samtidigt ställs det stora krav på transportsektorn att öka effektiviteten och minska miljöpåverkan vid transporter av både människor och varor. Som en följd av detta har många ledande fordonstillverkare och teknikföretag börjat satsat på att utveckla avancerade förarstödsystem och självkörande fordon. Även forskningen inom autonoma fordon har under de senaste årtiondena kraftig ökat då en rad tekniska problem återstår att lösas. Förarlösa fordon förväntas få sitt första stora genombrott i slutna miljöer, såsom gruvor, hamnar, lastnings- och lossningsplatser. I sådana områden är lagstiftningen mindre hård jämfört med stadsområden och omgivningen är mer kontrollerad och förutsägbar. Några av de förväntade positiva effekterna är ökad produktivitet och säkerhet, minskade utsläpp och möjligheten att avlasta människor från att utföra svåra eller farliga uppgifter. Inom dessa platser används ofta lastbilar med olika släpvagnskombinationer för att transportera material. En sådan fordonskombination är uppbyggd av flera ihopkopplade moduler och är således utmanande att backa då systemet är instabilt. Detta gör det svårt att utforma ramverk för att styra sådana system vid exempelvis autonom backning. Självkörande fordon är mycket komplexa system som består av en rad olika komponenter vilka är designade för att lösa separata delproblem. Två viktiga komponenter i ett självkörande fordon är dels rörelseplaneraren som har i uppgift att planera hur fordonet ska röra sig för att på ett säkert sätt nå ett överordnat mål, och dels den banföljande regulatorn vars uppgift är att se till att den planerade manövern faktiskt utförs i praktiken trots störningar och modellfel. I denna avhandling presenteras flera olika algoritmer för att planera och utföra komplexa manövrar för lastbilar med olika typer av släpvagnskombinationer. De presenterade algoritmerna är avsedda att användas som avancerade förarstödsystem eller som komponenter i ett helt autonomt system. Även om den primära applikationen i denna avhandling är lastbilar med släp, kan många av de förslagna algoritmerna även användas för en rad andra system, så som drönare och båtar. Experimentell validering är viktigt för att motivera att en föreslagen algoritm är användbar i praktiken. I denna avhandling har flera av de föreslagna planerings- och reglerstrategierna implementerats på en småskalig testplattform och utvärderats i en kontrollerad labbmiljö. Utöver detta har även flera av de föreslagna ramverken implementerats och utvärderats i fältexperiment på en fullskalig test-plattform som har utvecklats i samarbete med Scania CV. Här utvärderas även en ny metod för att skatta släpvagnens beteende genom att endast utnyttja information från sensorer monterade på lastbilen, vilket gör det föreslagna ramverket oberoende av sensorer monterade på släpvagnen.

Download or read book Motion and Operation Planning of Robotic Systems written by Giuseppe Carbone and published by Springer. This book was released on 2015-03-12 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the broad multi-disciplinary topic of robotics, and presents the basic techniques for motion and operation planning in robotics systems. Gathering contributions from experts in diverse and wide ranging fields, it offers an overview of the most recent and cutting-edge practical applications of these methodologies. It covers both theoretical and practical approaches, and elucidates the transition from theory to implementation. An extensive analysis is provided, including humanoids, manipulators, aerial robots and ground mobile robots. ‘Motion and Operation Planning of Robotic Systems’ addresses the following topics: *The theoretical background of robotics. *Application of motion planning techniques to manipulators, such as serial and parallel manipulators. *Mobile robots planning, including robotic applications related to aerial robots, large scale robots and traditional wheeled robots. *Motion planning for humanoid robots. An invaluable reference text for graduate students and researchers in robotics, this book is also intended for researchers studying robotics control design, user interfaces, modelling, simulation, sensors, humanoid robotics.

Download or read book Simultaneous Planning and Control for Autonomous Ground Vehicles written by Thomas C. Galluzzo and published by . This book was released on 2006 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Motion planning and control for autonomous vehicles are complex tasks that must be done in order for a ground robot to operate in a cluttered environment. This dissertation presents the theory, implementation, and test results for some new and novel Receding Horizon Control (RHC) techniques that allow these tasks to be unified into one. The first new method is called Heuristic Receding Horizon Control (HRHC), and uses a modified A* search to fulfill the online optimization required by RHC. The second is called Dual-Frequency Receding Horizon Control (DFRHC), and is used to simplify the trajectory planning process during the RHC optimization. Both methods are combined together to form a practical implementation, which is discussed in detail. The autonomous ground vehicle, the NaviGator, developed at the Center for Intelligent Machines and Robotics, serves as a platform for the implementation and testing discussed. Finally, data and their analysis are presented. The results obtained help to support the theoretical and practical claims made by this dissertation.

Download or read book Path Planning for Autonomous Vehicle written by Umar Zakir Abdul Hamid and published by BoD – Books on Demand. This book was released on 2019-10-02 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).

Download or read book Real time Obstacle Avoiding Motion Planning for Autonomous Ground Vehicles written by ji-Wung Choi and published by . This book was released on 2010 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Motion Planning for Autonomous Vehicles in Partially Observable Environments written by Taş, Ömer Şahin and published by KIT Scientific Publishing. This book was released on 2023-10-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Autonomous Vehicles in Support of Naval Operations written by National Research Council and published by National Academies Press. This book was released on 2005-08-05 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous vehicles (AVs) have been used in military operations for more than 60 years, with torpedoes, cruise missiles, satellites, and target drones being early examples.1 They have also been widely used in the civilian sector-for example, in the disposal of explosives, for work and measurement in radioactive environments, by various offshore industries for both creating and maintaining undersea facilities, for atmospheric and undersea research, and by industry in automated and robotic manufacturing. Recent military experiences with AVs have consistently demonstrated their value in a wide range of missions, and anticipated developments of AVs hold promise for increasingly significant roles in future naval operations. Advances in AV capabilities are enabled (and limited) by progress in the technologies of computing and robotics, navigation, communications and networking, power sources and propulsion, and materials. Autonomous Vehicles in Support of Naval Operations is a forward-looking discussion of the naval operational environment and vision for the Navy and Marine Corps and of naval mission needs and potential applications and limitations of AVs. This report considers the potential of AVs for naval operations, operational needs and technology issues, and opportunities for improved operations.

Download or read book Human Like Decision Making and Control for Autonomous Driving written by Peng Hang and published by CRC Press. This book was released on 2022-07-25 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios. Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios. The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.

Download or read book Learning Applied to Ground Vehicles written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-05-05 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Learning Applied to Ground Vehicles The Learning Applied to Ground Vehicles (LAGR) initiative, which was in operation from 2004 until 2008, was designed with the intention of expediting the development of autonomous, perception-based, off-road navigation in robotic unmanned ground vehicles (UGVs). DARPA, which is a research agency under the Department of Defense of the United States of America, provided funding for LAGR. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: DARPA LAGR Program Chapter 2: DARPA Chapter 3: Autonomous robot Chapter 4: Military robot Chapter 5: DARPA Grand Challenge Chapter 6: Unmanned ground vehicle Chapter 7: European Land-Robot Trial Chapter 8: Mobile robot Chapter 9: Crusher (robot) Chapter 10: National Robotics Engineering Center (II) Answering the public top questions about learning applied to ground vehicles. (III) Real world examples for the usage of learning applied to ground vehicles in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Learning Applied to Ground Vehicles.

Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating 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 platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.

Download or read book Motion Planning for Humanoid Robots written by Kensuke Harada and published by Springer. This book was released on 2014-12-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: • whole body motion planning, • task planning, • biped gait planning, and • sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

Download or read book The DARPA Urban Challenge written by Martin Buehler and published by Springer. This book was released on 2009-11-26 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.