Download or read book Environmental Perception Technology for Unmanned Systems written by Xin Bi and published by Springer Nature. This book was released on 2020-09-30 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the principles and technology of environmental perception in unmanned systems. With the rapid development of a new generation of information technologies such as automatic control and information perception, a new generation of robots and unmanned systems will also take on new importance. This book first reviews the development of autonomous systems and subsequently introduces readers to the technical characteristics and main technologies of the sensor. Lastly, it addresses aspects including autonomous path planning, intelligent perception and autonomous control technology under uncertain conditions. For the first time, the book systematically introduces the core technology of autonomous system information perception.

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.

Download or read book Robust Environmental Perception and Reliability Control for Intelligent Vehicles written by Huihui Pan (Of Haerbin gong ye da xue) and published by . This book was released on 2024 with total page 0 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."--

Download or read book Unmanned Aerial Remote Sensing written by David R. Green and published by CRC Press. This book was released on 2020-07-10 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aircraft Systems (UAS) are a rapidly evolving technology with an expanding array of diverse applications. In response to the continuing evolution of this technology, this book discusses unmanned aerial vehicles (UAVs) and similar systems, platforms and sensors, as well as exploring some of their environmental applications. It explains how they can be used for mapping, monitoring, and modeling a wide variety of different environmental aspects, and at the same time addresses some of the current constraints placed on realizing the potential use of the technology such as s flight duration and distance, safety, and the invasion of privacy etc. Features of the book: Provides necessary theoretical foundations for pertinent subject matter areas Introduces the role and value of UAVs for geographical data acquisition, and the ways to acquire and process the data Provides a synthesis of ongoing research and a focus on the use of technology for small-scale image and spatial data acquisition in an environmental context Written by experts of the technology who bring together UAS tools and resources for the environmental specialist Unmanned Aerial Remote Sensing: UAS for Environmental Applications is an excellent resource for any practitioner utilizing remote sensing and other geospatial technologies for environmental applications, such as conservation, research, and planning. Students and academics in information science, environment and natural resources, geosciences, and geography, will likewise find this comprehensive book a useful and informative resource.

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 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 Proceedings of 2022 International Conference on Autonomous Unmanned Systems ICAUS 2022 written by Wenxing Fu and published by Springer Nature. This book was released on 2023-03-10 with total page 3985 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the ICAUS 2022, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2022 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.

Download or read book UAV Sensors for Environmental Monitoring written by Felipe Gonzalez Toro and published by MDPI. This book was released on 2018-03-05 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "UAV Sensors for Environmental Monitoring" that was published in Sensors

Download or read book Uncertainty aware Spatiotemporal Perception for Autonomous Vehicles written by Mikhal Itkina and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous vehicles are set to revolutionize transportation in terms of safety and efficiency. However, autonomous systems still have challenges operating in complex human environments, such as an autonomous vehicle in a cluttered, dynamic urban setting. A key obstacle to deploying autonomous systems on the road is understanding, anticipating, and making inferences about human behaviors. Autonomous perception builds a general understanding of the environment for a robot. This includes making inferences about human behaviors in both space and time. Humans are difficult to model due to their vastly diverse behaviors and rapidly evolving objectives. Moreover, in cluttered settings, there are computational and visibility limitations. However, humans also possess desirable capabilities, such as their ability to generalize beyond their observed environment. Although learning-based systems have had success in recent years in modeling and imitating human behavior, efficiently capturing the data and model uncertainty for these systems remains an open problem. This thesis proposes algorithmic advances to uncertainty-aware autonomous perception systems in human environments. We make system-level contributions to spatiotemporal robot perception that reasons about human behavior, and foundational advancements in uncertainty-aware machine learning models for trajectory prediction. These contributions enable robotic systems to make uncertainty- and socially-aware spatiotemporal inferences about human behavior. Traditional robot perception is object-centric and modular, consisting of object detection, tracking, and trajectory prediction stages. These systems can fail prior to the prediction stage due to partial occlusions in the environment. We thus propose an alternative end-to-end paradigm for spatiotemporal environment prediction from a map-centric occupancy grid representation. Occupancy grids are robust to partial occlusions, can handle an arbitrary number of human agents in the scene, and do not require a priori information regarding the environment. We investigate the performance of computer vision techniques in this context and develop new mechanisms tailored to the task of spatiotemporal environment prediction. Spatially, robots also need to reason about fully occluded agents in their environment, which may occur due to sensor limitations or other agents on the road obstructing the field of view. Humans excel at extrapolating from their experiences by making inferences from observed social behaviors. We draw inspiration from human intuition to fill in portions of the robot's map that are not observable by traditional sensors. We infer occupancy in these occluded regions by learning a multimodal mapping from observed human driver behaviors to the environment ahead of them, thus treating people as sensors. Our system handles multiple observed agents to maximally inform the occupancy map around the robot. In order to safely integrate human behavior modeling into the robot autonomy stack, the perception system must efficiently account for uncertainty. Human behavior is often modeled using discrete latent spaces in learning-based models to capture the multimodality in the distribution. For example, in a trajectory prediction task, there may be multiple valid future predictions given a past trajectory. To accurately model this latent distribution, the latent space needs to be sufficiently large, leading to tractability concerns for downstream tasks, such as path planning. We address this issue by proposing a sparsification algorithm for discrete latent sample spaces that can be applied post hoc without sacrificing model performance. Our approach successfully balances multimodality and sparsity to achieve efficient data uncertainty estimation. Aside from modeling data uncertainty, learning-based autonomous systems must be aware of their model uncertainty or what they do not know. Flagging out-of-distribution or unknown scenarios encountered in the real world could be helpful to downstream autonomy stack components and to engineers for further system development. Although the machine learning community has been prolific in model uncertainty estimation for small benchmark problems, relatively little work has been done on estimating this uncertainty in complex, learning-based robotic systems. We propose efficiently learning the model uncertainty over an interpretable, low-dimensional latent space in the context of a trajectory prediction task. The algorithms presented in this thesis were validated on real-world autonomous driving data and baselined against state-of-the-art techniques. We show that drawing inspiration from human-level reasoning while modeling the associated uncertainty can inform environment understanding for autonomous perception systems. The contributions made in this thesis are a step towards uncertainty- and socially-aware autonomous systems that can function seamlessly in human environments.

Download or read book Big Data Transportation Systems written by Guanghui Zhao and published by World Scientific. This book was released on 2021-07-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a popular science book on big data analytics in intelligent transportation systems. It aims to provide an introduction to big-data transportation starting from an overview on the development of big data transportation in various countries. This is followed by a discussion on the blueprint strategies of big data transportation which include innovative models, planning, transportation logistics, and application case studies. Finally, the book discusses applications of big data transportation platforms.

Download or read book Remote Sensing and Actuation Using Unmanned Vehicles written by Haiyang Chao and published by John Wiley & Sons. This book was released on 2012-08-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.

Download or read book Scanning Technologies for Autonomous Systems written by Julio C. Rodríguez-Quiñonez and published by Springer Nature. This book was released on with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of UASG 2021 Wings 4 Sustainability written by Kamal Jain and published by Springer Nature. This book was released on 2023-03-15 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume gathers the latest advances, innovations, and applications in the field of geographic information systems and unmanned aerial vehicle (UAV) technologies, as presented by leading researchers and engineers at the 2nd International Conference on Unmanned Aerial System in Geomatics (UASG), held in Roorkee, India on April 2-4, 2021. It covers highly diverse topics, including photogrammetry and remote sensing, surveying, UAV manufacturing, geospatial data sensing, UAV processing, visualization, and management, UAV applications and regulations, geo-informatics and geomatics. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists.

Download or read book Proceedings of the 4th International Conference on Big Data Analytics for Cyber Physical System in Smart City Volume 1 written by Mohammed Atiquzzaman and published by Springer Nature. This book was released on 2023-07-04 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the 4th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2022) conference, held in Bangkok, Thailand, on December 16–17. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Download or read book Urban Environment Perception and Navigation Using Robotic Vision written by Giovani Bernardes Vitor and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of autonomous vehicles capable of getting around on urban roads can provide important benefits in reducing accidents, in increasing life comfort and also in providing cost savings. Intelligent vehicles for example often base their decisions on observations obtained from various sensors such as LIDAR, GPS and Cameras. Actually, camera sensors have been receiving large attention due to they are cheap, easy to employ and provide rich data information. Inner-city environments represent an interesting but also very challenging scenario in this context,where the road layout may be very complex, the presence of objects such as trees, bicycles,cars might generate partial observations and also these observations are often noisy or even missing due to heavy occlusions. Thus, perception process by nature needs to be able to dea lwith uncertainties in the knowledge of the world around the car. While highway navigation and autonomous driving using a prior knowledge of the environment have been demonstrating successfully,understanding and navigating general inner-city scenarios with little prior knowledge remains an unsolved problem. In this thesis, this perception problem is analyzed for driving in the inner-city environments associated with the capacity to perform a safe displacement basedon decision-making process in autonomous navigation. It is designed a perception system that allows robotic-cars to drive autonomously on roads, with out the need to adapt the infrastructure,without requiring previous knowledge of the environment and considering the presenceof dynamic objects such as cars. It is proposed a novel method based on machine learning to extract the semantic context using a pair of stereo images, which is merged in an evidential grid to model the uncertainties of an unknown urban environment, applying the Dempster-Shafer theory. To make decisions in path-planning, it is applied the virtual tentacle approach to generate possible paths starting from ego-referenced car and based on it, two news strategies are proposed. First one, a new strategy to select the correct path to better avoid obstacles and tofollow the local task in the context of hybrid navigation, and second, a new closed loop control based on visual odometry and virtual tentacle is modeled to path-following execution. Finally, a complete automotive system integrating the perception, path-planning and control modules are implemented and experimentally validated in real situations using an experimental autonomous car, where the results show that the developed approach successfully performs a safe local navigation based on camera sensors.

Download or read book Advanced Manufacturing and Automation XII written by Yi Wang and published by Springer Nature. This book was released on 2023-01-25 with total page 905 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of selected papers from the 12th International Workshop of Advanced Manufacturing and Automation (IWAMA 2022), held in Jimei University, Xiamen, China on 01 - 02 November, 2022. Topics focusing on novel techniques for manufacturing and automation in Industry 4.0 are now vital factors for the maintenance and improvement of the economy of a nation and the quality of life. It will help academic researchers and engineering to implement the concept, theory and methods in Industry 4.0 which has been a hot topic. These proceedings will make valuable contributions to academic researchers, engineers in the industry for the challenges in the 4th industry revolution and smart factories.

Download or read book Environmental Perception for Automated Vehicles written by Jae Bum Choi and published by Cuvillier Verlag. This book was released on 2016-05-26 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the issues of the environmental perception for automated vehicles. The environment which the vehicle has to perceive can be generally classified into two groups: stationary and movable objects. The perception is to represent and understand these environments by organizing, identifying, and interpreting sensory information. Firstly, the sensory information is obtained based on the vehicle pose (position and orientation), and therefore the environmental perception necessarily includes a localization task. Then, the stationary objects are generally represented with a map, and the movable objects are tracked to represent their temporal behaviors. These environmental perception tasks can be summarized into two well known technical problems: simultaneous localization and mapping (SLAM), and detection and tracking of movable objects (DATMO). In this thesis, a novel framework to solve these problems by using Velodyne laser scanner is presented.