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On Semantic Segmentation And Path Planning For Autonomous Vehicles Within Off Road Environments
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Book Synopsis On Semantic Segmentation and Path Planning for Autonomous Vehicles Within Off-road Environments by : Christopher John Holder
Download or read book On Semantic Segmentation and Path Planning for Autonomous Vehicles Within Off-road Environments written by Christopher John Holder and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Path Planning for Autonomous Vehicle by : Umar Zakir Abdul Hamid
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 ).
Book Synopsis Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by : Muhammad Aizzat Zakaria
Download or read book Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver written by Muhammad Aizzat Zakaria and published by . This book was released on 2019 with total page 148 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 ).
Book Synopsis Path Planning for Vehicles Operating in Uncertain 2D Environments by : Viacheslav Pshikhopov
Download or read book Path Planning for Vehicles Operating in Uncertain 2D Environments written by Viacheslav Pshikhopov and published by Butterworth-Heinemann. This book was released on 2017-01-28 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes. Presents a survey of accounting limitations imposed by vehicle dynamics Proposes modified and new original methods, including neural networking, grapho-analytical, and nature-inspired Gives tools for a novice researcher to select a method that would suit their needs or help to synthesize new hybrid methods
Book Synopsis Robust Environmental Perception and Reliability Control for Intelligent Vehicles by : Huihui Pan
Download or read book Robust Environmental Perception and Reliability Control for Intelligent Vehicles written by Huihui Pan and published by Springer Nature. This book was released on 2023-11-25 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes. Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy. Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods. Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers. Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account. Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
Book Synopsis Performance Enhancement of Wide-range Perception Issues for Autonomous Vehicles by : Suvash Sharma
Download or read book Performance Enhancement of Wide-range Perception Issues for Autonomous Vehicles written by Suvash Sharma and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the mission-critical nature of the autonomous driving application, underlying algorithms for scene understanding should be given special care during their development. Mostly, they should be designed with precise consideration of accuracy and run-time. Accuracy should be considered strictly which if compromised leads to faulty interpretation of the environment that may ultimately result in accidental scenarios. On the other hand, run-time holds an important position as the delayed understanding of the scene would hamper the real-time response of the vehicle which again leads to unforeseen accidental cases. These factors come as the functions of several factors such as the design and complexity of the algorithms, nature of the encountered objects or events in the environment, weather-induced effects, etc. In this work, several novel scene understanding algorithms in terms- of semantic segmentation are devised. First, a transfer learning technique is proposed in order to transfer the knowledge from the data-rich domain to a data-scarce off-road driving domain for semantic segmentation such that the learned information is efficiently transferred from one domain to another while reducing run-time and increasing the accuracy. Second, the performance of several segmentation algorithms is assessed under the easy-to-severe rainy condition and two methods for achieving the robustness are proposed. Third, a new method of eradicating the rain from the input images is proposed. Since autonomous vehicles are rich in sensors and each of them has the capability of representing different types of information, it is worth fusing the information from all the possible sensors. Forth, a fusion mechanism with a novel algorithm that facilitates the use of local and non-local attention in a cross-modal scenario with RGB camera images and lidar-based images for road detection using semantic segmentation is executed and validated for different driving scenarios. Fifth, a conceptually new method of off-road driving trail representation, called Traversability, is introduced. To establish the correlation between a vehicle’s capability and the level of difficulty of the driving trail, a new dataset called CaT (CAVS Traversability) is introduced. This dataset is very helpful for future research in several off-road driving applications including military purposes, robotic navigation, etc.
Book Synopsis Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by : Muhammad Aizzat Zakaria
Download or read book Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver written by Muhammad Aizzat Zakaria and published by . This book was released on 2019 with total page 148 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 ).
Book Synopsis Trajectory Planning of an Autonomous Vehicle in Multi-Vehicle Traffic Scenarios by : Mahdi Morsali
Download or read book Trajectory Planning of an Autonomous Vehicle in Multi-Vehicle Traffic Scenarios written by Mahdi Morsali and published by Linköping University Electronic Press. This book was released on 2021-03-25 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tremendous industrial and academic progress and investments have been made in au-tonomous driving, but still many aspects are unknown and require further investigation,development and testing. A key part of an autonomous driving system is an efficient plan-ning algorithm with potential to reduce accidents, or even unpleasant and stressful drivingexperience. A higher degree of automated planning also makes it possible to have a betterenergy management strategy with improved performance through analysis of surroundingenvironment of autonomous vehicles and taking action in a timely manner. This thesis deals with planning of autonomous vehicles in different urban scenarios, road,and vehicle conditions. The main concerns in designing the planning algorithms, are realtime capability, safety and comfort. The planning algorithms developed in this thesis aretested in simulation traffic situations with multiple moving vehicles as obstacles. The re-search conducted in this thesis falls mainly into two parts, the first part investigates decou-pled trajectory planning algorithms with a focus on speed planning, and the second sectionexplores different coupled planning algorithms in spatiotemporal environments where pathand speed are calculated simultaneously. Additionally, a behavioral analysis is carried outto evaluate different tactical maneuvers the autonomous vehicle can have considering theinitial states of the ego and surrounding vehicles. Particularly relevant for heavy duty vehicles, the issues addressed in designing a safe speedplanner in the first part are road conditions such as banking, friction, road curvature andvehicle characteristics. The vehicle constraints on acceleration, jerk, steering, steer ratelimitations and other safety limitations such as rollover are further considerations in speedplanning algorithms. For real time purposes, a minimum working roll model is identified us-ing roll angle and lateral acceleration data collected in a heavy duty truck. In the decoupledplanners, collision avoiding is treated using a search and optimization based planner. In an autonomous vehicle, the structure of the road network is known to the vehicle throughmapping applications. Therefore, this key property can be used in planning algorithms toincrease efficiency. The second part of the thesis, is focused on handling moving obstaclesin a spatiotemporal environment and collision-free planning in complex urban structures.Spatiotemporal planning holds the benefits of exhaustive search and has advantages com-pared to decoupled planning, but the search space in spatiotemporal planning is complex.Support vector machine is used to simplify the search problem to make it more efficient.A SVM classifies the surrounding obstacles into two categories and efficiently calculate anobstacle free region for the ego vehicle. The formulation achieved by solving SVM, con-tains information about the initial point, destination, stationary and moving obstacles.These features, combined with smoothness property of the Gaussian kernel used in SVMformulation is proven to be able to solve complex planning missions in a safe way. Here, three algorithms are developed by taking advantages of SVM formulation, a greedysearch algorithm, an A* lattice based planner and a geometrical based planner. One general property used in all three algorithms is reduced search space through using SVM. In A*lattice based planner, significant improvement in calculation time, is achieved by using theinformation from SVM formulation to calculate a heuristic for planning. Using this heuristic,the planning algorithm treats a simple driving scenario and a complex urban structureequal, as the structure of the road network is included in SVM solution. Inspired byobserving significant improvements in calculation time using SVM heuristic and combiningthe collision information from SVM surfaces and smoothness property, a geometrical planneris proposed that leads to further improvements in calculation time. Realistic driving scenarios such as roundabouts, intersections and takeover maneuvers areused, to test the performance of the proposed algorithms in simulation. Different roadconditions with large banking, low friction and high curvature, and vehicles prone to safetyissues, specially rollover, are evaluated to calculate the speed profile limits. The trajectoriesachieved by the proposed algorithms are compared to profiles calculated by optimal controlsolutions.
Book Synopsis Creating Autonomous Vehicle Systems by : Shaoshan Liu
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.
Book Synopsis Multiple-path Generation to Improve Autonomous Vehicle Planning by : Vishnu Penubarthi
Download or read book Multiple-path Generation to Improve Autonomous Vehicle Planning written by Vishnu Penubarthi and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path planning is an integral part of ensuring autonomous vehicles become more safe and efficient in order to facilitate greater adoption of the technology and make it a viable option for an increased number of applications. While there are many documented approaches to path planning on roads, the challenge of path planning in an off-road environment is less studied and presents additional challenges including traversing an unknown and unstructured map environment. This can result in scenarios where previously unknown obstacles are discovered along a path a vehicle is traversing, forcing the vehicle to re-route and take a potentially inefficient route to its final destination. We present an extensible framework to mitigate this issue in which we generate multiple paths, select an efficient path for the vehicle with respect to its navigation to the final destination, and incentivize the vehicle to adhere to the selected path. We also implement this framework within the Nebula team's ROS-based autonomous vehicle software stack for DARPA's Racer challenge and compare its performance to the current implementation. Through testing performed in simulation on topologies of interest to the Nebula group, we find that the proposed framework results in a 37% increase in average speed and a 24% decrease in time to reach the final destination compared to the current implementation.
Book Synopsis Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023) by : Yi Qu
Download or read book Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023) written by Yi Qu and published by Springer Nature. This book was released on with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Experimental Robotics by : Marcelo H. Ang Jr
Download or read book Experimental Robotics written by Marcelo H. Ang Jr and published by Springer Nature. This book was released on with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Path-Planning and Optimization of a High-speed 1/5-Scale Off-Road Autonomous Vehicle by : Andres Esparragoza
Download or read book Path-Planning and Optimization of a High-speed 1/5-Scale Off-Road Autonomous Vehicle written by Andres Esparragoza and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis investigates path-planning for a high-speed off-road autonomous vehicle. A 1/5th scale Remote Control (RC) vehicle was modified with sensors to be able to track vehicle position, trajectory, velocity, and other parameters necessary while performing traversals on a specifically designed off-road course that challenges the vehicles maneuverability and velocity. Advanced global position system (GPS) and encoder algorithms are implemented into the vehicles onboard microcontrollers to determine real time data necessary to dictate the necessary steering and throttle inputs. The sensor algorithms allow for the vehicle to measure its position and velocity, thereby enabling the foundation of path-following. Using algorithms to control the two receiving functions, steering and throttle, the vehicle must traverse the course autonomously with the aim of increasing speed per traversal until reaching an optimal steady-state velocity profile. Using iterative learning control (ILC) and similar control strategies, the vehicle learns from prior traversals to find limiting levels of velocity to be able to repeatedly produce traversals faster with each lap. The foundation for a 1/5th scale high-speed off-road vehicle path following simulation is created on MATLAB prior to vehicle implementation. The simulation successfully models constant speed along a path for both large-scale and 1/5th scale vehicles. The simulation is prepared for the implementation of ILC to determine the optimal steady-state velocity profile. The goal is for the simulation to achieve lap navigation faster than if a human were to control the vehicle via its remote-control unit. This research discussion concludes by outlining the next steps for algorithm development and field testing. The overall goal is to contribute to the development of autonomous off-road vehicles for use in a range of applications, including agriculture, mining, and search and rescue. The findings of this thesis seek to advance core algorithms and deployment technologies for autonomous systems in challenging off-road environments.
Book Synopsis Path Planning, Replanning, and Execution for Autonomous Driving in Urban and Offroad Environments by : Roland Philippsen
Download or read book Path Planning, Replanning, and Execution for Autonomous Driving in Urban and Offroad Environments written by Roland Philippsen and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Path Planning for Autonomous Vehicles in Difficult Unstructured Environments by : Alexander Russell Green
Download or read book Path Planning for Autonomous Vehicles in Difficult Unstructured Environments written by Alexander Russell Green and published by . This book was released on 2007 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear Model Predictive Control by : Frank Allgöwer
Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.
Book Synopsis Path Planning for Autonomous Vehicle in Off-Road Scenario by : Haiping Du
Download or read book Path Planning for Autonomous Vehicle in Off-Road Scenario written by Haiping Du and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The road topography information, such as bank angle and road slope, can significantly affect the trajectory tracking performance of the autonomous vehicle, so this information needs to be considered in the trajectory planning and tracking control for off-road autonomous vehicle. In this chapter, a two-level real-time dynamically integrated spatiotemporal-based trajectory planning and control method for off-road autonomous vehicle is proposed. In the upper-level trajectory planner, the most suitable time-parameterised trajectory with the minimum values of road slope and bank angle can be selected from a set of candidate trajectories. In the lower-level trajectory tracking controller, the sliding-mode control (SMC) technique is applied to control the vehicle and achieve the desired trajectory. Finally, simulation results are presented to verify the proposed integrated trajectory planning and control method and prove that the proposed integrated method has better overall tracking control and dynamics control performance than the conventional method both in the highway scenario and off-road scenario. Furthermore, the four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID) vehicle shows better tracking control performance than vehicle based on two-wheel model.
