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This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

n/a --- FPGA --- recurrence plot (RP) --- residual learning --- neural networks --- driver monitoring --- navigation --- depthwise separable convolution --- optimization --- dynamic path-planning algorithms --- object tracking --- sub-region --- cooperative systems --- convolutional neural networks --- DSRC --- VANET --- joystick --- road scene --- convolutional neural network (CNN) --- multi-sensor --- p-norm --- occlusion --- crash injury severity prediction --- deep leaning --- squeeze-and-excitation --- electric vehicles --- perception in challenging conditions --- T-S fuzzy neural network --- total vehicle mass of the front vehicle --- electrocardiogram (ECG) --- communications --- generative adversarial nets --- camera --- adaptive classifier updating --- Vehicle-to-X communications --- convolutional neural network --- predictive --- Geobroadcast --- infinity norm --- urban object detector --- machine learning --- automated-manual transition --- red light-running behaviors --- photoplethysmogram (PPG) --- panoramic image dataset --- parallel architectures --- visual tracking --- autopilot --- ADAS --- kinematic control --- GPU --- road lane detection --- obstacle detection and classification --- Gabor convolution kernel --- autonomous vehicle --- Intelligent Transport Systems --- driving decision-making model --- Gaussian kernel --- autonomous vehicles --- enhanced learning --- ethical and legal factors --- kernel based MIL algorithm --- image inpainting --- fusion --- terrestrial vehicle --- driverless --- drowsiness detection --- map generation --- object detection --- interface --- machine vision --- driving assistance --- blind spot detection --- deep learning --- relative speed --- autonomous driving assistance system --- discriminative correlation filter bank --- recurrent neural network --- emergency decisions --- LiDAR --- real-time object detection --- vehicle dynamics --- path planning --- actuation systems --- maneuver algorithm --- autonomous driving --- smart band --- the emergency situations --- two-wheeled --- support vector machine model --- global region --- biological vision --- automated driving

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Unmanned aerial vehicles (UAVs) are being increasingly used in different applications in both military and civilian domains. These applications include surveillance, reconnaissance, remote sensing, target acquisition, border patrol, infrastructure monitoring, aerial imaging, industrial inspection, and emergency medical aid. Vehicles that can be considered autonomous must be able to make decisions and react to events without direct intervention by humans. Although some UAVs are able to perform increasingly complex autonomous manoeuvres, most UAVs are not fully autonomous; instead, they are mostly operated remotely by humans. To make UAVs fully autonomous, many technological and algorithmic developments are still required. For instance, UAVs will need to improve their sensing of obstacles and subsequent avoidance. This becomes particularly important as autonomous UAVs start to operate in civilian airspaces that are occupied by other aircraft. The aim of this volume is to bring together the work of leading researchers and practitioners in the field of unmanned aerial vehicles with a common interest in their autonomy. The contributions that are part of this volume present key challenges associated with the autonomous control of unmanned aerial vehicles, and propose solution methodologies to address such challenges, analyse the proposed methodologies, and evaluate their performance.

n/a --- super twisting sliding mode controller (STSMC) --- monocular visual SLAM --- modulation --- bio-inspiration --- simulation --- horizontal control --- sensor fusion --- ADRC --- high-order sliding mode --- over-the-horizon air confrontation --- longitudinal motion model --- autonomous control --- real-time ground vehicle detection --- maneuver decision --- nonlinear dynamics --- UAV automatic landing --- harmonic extended state observer --- image processing --- General Visual Inspection --- actuator faults --- actuator fault --- remote sensing --- aerial infrared imagery --- agricultural UAV --- SC-FDM --- tilt rotors --- mass eccentricity --- wind disturbance --- decoupling algorithm --- adaptive discrete mesh --- disturbance --- super twisting extended state observer (STESO) --- heuristic exploration --- sliding mode control --- UAS --- Q-Network --- UAV communication system --- UAV --- reinforcement learning --- autonomous landing area selection --- peak-to-average power ratio (PAPR) --- slung load --- aircraft maintenance --- flight mechanics --- octree --- unmanned aerial vehicle --- convolutional neural network --- aircraft --- performance evaluation --- quadrotor --- vertical take off --- data link --- path planning --- coaxial-rotor --- fixed-time extended state observer (FTESO) --- multi-UAV system --- hardware-in-the-loop --- distributed swarm control --- vertical control

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Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations.

Technology: general issues --- History of engineering & technology --- physical human-robot interaction --- game theory --- adaptive optimal control --- robot control --- tandem force sensor --- traction force sensor --- human–robot interaction --- contact task --- imitation learning --- safe physical human–robot collaboration --- collision detection --- human action recognition --- artificial intelligence --- industrial automation --- reinforcement learning --- social robotics --- human-robot interaction --- reward design --- physical embodiment --- human robot collaboration --- human robot interaction --- path planning --- bidirectional awareness --- haptic feedback device --- human machine interface --- collision identification --- collaborative robot --- deep learning --- uncertainty estimation --- knowledge distillation --- human–robot collaboration --- speed and separation monitoring --- human–machine differentiation --- thermal cameras --- protective separation distance --- collaborative robots --- motion planning --- human motion prediction --- human-following robots --- teleoperation --- high-speed image processing --- machine learning --- finger position recognition --- grasp type estimation --- human-robot collaboration --- human-centered robotics --- task planning --- n/a --- safe physical human-robot collaboration --- human-machine differentiation

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The Industry 4.0 paradigm has led to the creation of new opportunities for taking advantage of a set of diverse technologies in the manufacturing domain. This book touches on a series of advanced technologies and research fields, including Internet of Things, Augmented and Virtual Reality, Machine Learning, Advanced Robotics, Additive Manufacturing, System and Process Simulation, Computer-Aided Design/Engineering/Manufacturing/Process Planning Systems as well as Product Lifecycle Management Platforms. The topics covered span a series of diverse areas related to a) product design and development, b) manufacturing systems and operations, c) process engineering, and d) Industry 4.0 technologies review and realization.

History of engineering & technology --- computer-aided tolerance --- processing features degradation --- skin model shape --- statistical tolerance analysis --- tolerance allocation --- collaborative learning --- engineering graphics --- PLM --- 3D modeling --- engineering education --- Industry 4.0 --- index --- smart --- intensity of technology --- manufacturing --- implementation --- statistical process control --- pattern recognition --- long short-term memory --- feature learning --- control chart --- histogram --- digital hydraulic technology --- digital hydraulic components --- digital hydraulic system --- shearer --- virtual reality --- path planning --- automatic height-adjusting --- Unity3D technology --- Rapidly-exploring Random Tree (RRT) --- manipulator --- motion planning --- obstacle avoidance --- complex environment --- exoskeletons --- planning methods --- ergonomics --- time management --- augmented reality --- maintenance --- real-time --- digital twin --- decision support system --- factor analysis --- KPI --- quantitative analysis --- root-cause analysis --- life cycle --- knowledge- and technology-intensive industry (KTI) --- VUCA --- key enabling technology (KET) --- Operator 4.0 --- cyber-physical system (CPS) --- DfHFinI4.0 --- PERA 4.0 --- process planning --- scheduling --- design for additive manufacturing --- multiple criteria --- SMEs --- technologies --- cluster analysis --- maturity model --- n/a

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Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. It consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.

Technology: general issues --- History of engineering & technology --- LiDAR --- RetinaNet --- inception --- Mobile Laser Scanning --- point clouds --- data fusion --- Lidar --- point cloud density --- point cloud coverage --- mobile mapping systems --- 3D simulation --- Pandar64 --- Ouster OS-1-64 --- mobile laser scanning --- lever arm --- boresight angles --- plane-based calibration field --- configuration analysis --- accuracy --- controllability --- evaluation --- control points --- TLS reference point clouds --- visual–inertial odometry --- Helmert variance component estimation --- line feature matching method --- correlation coefficient --- point and line features --- mobile mapping --- manhole cover --- point cloud --- F-CNN --- transfer learning --- CAM localization --- loop closure detection --- visual SLAM --- semantic topology graph --- graph matching --- CNN features --- deep learning --- view planning --- imaging network design --- building 3D modelling --- path planning --- V-SLAM --- real-time --- guidance --- embedded-systems --- 3D surveying --- exposure control --- photogrammetry --- parking statistics --- vehicle detection --- robot operating system --- 3D camera --- RGB-D --- performance evaluation --- convolutional neural networks --- smart city --- georeferencing --- MSS --- IEKF --- DSIEKF --- geometrical constraints --- 6-DoF --- DTM --- 3D city model --- dataset --- laser scanning --- 3D mapping --- synthetic --- outdoor --- semantic --- scene completion