Narrow your search

Library

FARO (2)

KU Leuven (2)

LUCA School of Arts (2)

Odisee (2)

Thomas More Kempen (2)

Thomas More Mechelen (2)

UCLL (2)

ULB (2)

ULiège (2)

VIVES (2)

More...

Resource type

book (6)


Language

English (6)


Year
From To Submit

2021 (6)

Listing 1 - 6 of 6
Sort by

Book
Indoor Positioning and Navigation
Author:
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.

Keywords

Technology: general issues --- Energy industries & utilities --- dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion --- dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion


Book
UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection.

Keywords

Technology: general issues --- UAV --- landing --- optical flow --- video navigation --- Kalman filter --- coastal mapping --- coastal monitoring --- Digital Elevation Models (DEMs) --- geomorphological evolution --- photogrammetry --- Structure-from-Motion (SfM) --- Unmanned Aerial Vehicles (UAVs) --- snow mapping --- UAS --- remote sensing --- direct georeferencing --- snow field --- snow-covered area --- snow depth --- water level changes --- UAV photogrammetry --- tidal phase --- GNSS --- Kilim River --- unmanned aerial vehicles --- UAV swarms --- visual detection --- visual tracking --- machine vision --- deep learning --- YOLO --- laser guidance --- emergency landing --- particle filter --- change detection --- convolutional neural networks --- moving camera --- image alignment --- multirotor --- ground effect --- sensor faults --- UAV imagery --- bundle block adjustment --- digital surface model --- orthomosaic --- data collection --- accuracy --- technical guidelines --- DSM assessment --- backpack mobile mapping --- underground cellars --- unmanned aerial vehicle --- unmanned aerial system --- vision-based navigation --- search and rescue --- vision and action --- OODA --- inspection --- target detection --- autonomous localization --- 3D registration --- GPS-denied environment --- real-time --- multi-robot --- bioinspired map --- topologic mapping --- map exploration --- onboard GNSS RTK --- UAS traffic management --- multiple UAV navigation --- navigation in GPS/GNSS-denied environments --- distributed state estimation --- consensus theory --- computer architecture --- decision making --- navigation --- semantics --- aerial systems --- applications, inspection robotics, bridge inspection with UAS --- POMDP --- Deep Reinforcement-Learning --- multi-agent --- search --- UAV --- landing --- optical flow --- video navigation --- Kalman filter --- coastal mapping --- coastal monitoring --- Digital Elevation Models (DEMs) --- geomorphological evolution --- photogrammetry --- Structure-from-Motion (SfM) --- Unmanned Aerial Vehicles (UAVs) --- snow mapping --- UAS --- remote sensing --- direct georeferencing --- snow field --- snow-covered area --- snow depth --- water level changes --- UAV photogrammetry --- tidal phase --- GNSS --- Kilim River --- unmanned aerial vehicles --- UAV swarms --- visual detection --- visual tracking --- machine vision --- deep learning --- YOLO --- laser guidance --- emergency landing --- particle filter --- change detection --- convolutional neural networks --- moving camera --- image alignment --- multirotor --- ground effect --- sensor faults --- UAV imagery --- bundle block adjustment --- digital surface model --- orthomosaic --- data collection --- accuracy --- technical guidelines --- DSM assessment --- backpack mobile mapping --- underground cellars --- unmanned aerial vehicle --- unmanned aerial system --- vision-based navigation --- search and rescue --- vision and action --- OODA --- inspection --- target detection --- autonomous localization --- 3D registration --- GPS-denied environment --- real-time --- multi-robot --- bioinspired map --- topologic mapping --- map exploration --- onboard GNSS RTK --- UAS traffic management --- multiple UAV navigation --- navigation in GPS/GNSS-denied environments --- distributed state estimation --- consensus theory --- computer architecture --- decision making --- navigation --- semantics --- aerial systems --- applications, inspection robotics, bridge inspection with UAS --- POMDP --- Deep Reinforcement-Learning --- multi-agent --- search


Book
Indoor Positioning and Navigation
Author:
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.

Keywords

Technology: general issues --- Energy industries & utilities --- dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion --- n/a


Book
UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection.

Keywords

Technology: general issues --- UAV --- landing --- optical flow --- video navigation --- Kalman filter --- coastal mapping --- coastal monitoring --- Digital Elevation Models (DEMs) --- geomorphological evolution --- photogrammetry --- Structure-from-Motion (SfM) --- Unmanned Aerial Vehicles (UAVs) --- snow mapping --- UAS --- remote sensing --- direct georeferencing --- snow field --- snow-covered area --- snow depth --- water level changes --- UAV photogrammetry --- tidal phase --- GNSS --- Kilim River --- unmanned aerial vehicles --- UAV swarms --- visual detection --- visual tracking --- machine vision --- deep learning --- YOLO --- laser guidance --- emergency landing --- particle filter --- change detection --- convolutional neural networks --- moving camera --- image alignment --- multirotor --- ground effect --- sensor faults --- UAV imagery --- bundle block adjustment --- digital surface model --- orthomosaic --- data collection --- accuracy --- technical guidelines --- DSM assessment --- backpack mobile mapping --- underground cellars --- unmanned aerial vehicle --- unmanned aerial system --- vision-based navigation --- search and rescue --- vision and action --- OODA --- inspection --- target detection --- autonomous localization --- 3D registration --- GPS-denied environment --- real-time --- multi-robot --- bioinspired map --- topologic mapping --- map exploration --- onboard GNSS RTK --- UAS traffic management --- multiple UAV navigation --- navigation in GPS/GNSS-denied environments --- distributed state estimation --- consensus theory --- computer architecture --- decision making --- navigation --- semantics --- aerial systems --- applications, inspection robotics, bridge inspection with UAS --- POMDP --- Deep Reinforcement-Learning --- multi-agent --- search


Book
Indoor Positioning and Navigation
Author:
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot.

Keywords

dynamic objects identification and localization --- laser cluster --- radial velocity similarity --- Pearson correlation coefficient --- particle filter --- trilateral indoor positioning --- RSSI filter --- RSSI classification --- stability --- accuracy --- inertial navigation system --- artificial neural network --- motion tracking --- sensor fusion --- indoor navigation system --- indoor positioning --- indoor navigation --- radiating cable --- leaky feeder --- augmented reality --- Bluetooth --- indoor positioning system --- smart hospital --- indoor --- positioning --- visually impaired --- deep learning --- multi-layered perceptron --- inertial sensor --- smartphone --- multi-variational message passing (M-VMP) --- factor graph (FG) --- second-order Taylor expansion --- cooperative localization --- joint estimation of position and clock --- RTLS --- indoor positioning system (IPS) --- position data --- industry 4.0 --- traceability --- product tracking --- fingerprinting localization --- Bluetooth low energy --- Wi-Fi --- performance metrics --- positioning algorithms --- location source optimization --- fuzzy comprehensive evaluation --- DCPCRLB --- UAV --- unmanned aerial vehicles --- NWPS --- indoor positioning systems --- GPS denied --- GNSS denied --- autonomous vehicles --- visible light positioning --- mobile robot --- calibration --- appearance-based localization --- computer vision --- Gaussian processes --- manifold learning --- robot vision systems --- image manifold --- descriptor manifold --- indoor fingerprinting localization --- Gaussian filter --- Kalman filter --- received signal strength indicator --- channel state information --- indoor localization --- visual-inertial SLAM --- constrained optimization --- path loss model --- particle swarm optimization --- beacon --- absolute position system --- cooperative algorithm --- intercepting vehicles --- robot framework --- UWB sensors --- Internet of Things (IoT) --- wireless sensor network (WSN) --- switched-beam antenna --- electronically steerable parasitic array radiator (ESPAR) antenna --- received signal strength (RSS) --- fingerprinting --- down-conversion --- GPS --- navigation --- RF repeaters --- up-conversion --- n/a


Book
UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection.

Keywords

UAV --- landing --- optical flow --- video navigation --- Kalman filter --- coastal mapping --- coastal monitoring --- Digital Elevation Models (DEMs) --- geomorphological evolution --- photogrammetry --- Structure-from-Motion (SfM) --- Unmanned Aerial Vehicles (UAVs) --- snow mapping --- UAS --- remote sensing --- direct georeferencing --- snow field --- snow-covered area --- snow depth --- water level changes --- UAV photogrammetry --- tidal phase --- GNSS --- Kilim River --- unmanned aerial vehicles --- UAV swarms --- visual detection --- visual tracking --- machine vision --- deep learning --- YOLO --- laser guidance --- emergency landing --- particle filter --- change detection --- convolutional neural networks --- moving camera --- image alignment --- multirotor --- ground effect --- sensor faults --- UAV imagery --- bundle block adjustment --- digital surface model --- orthomosaic --- data collection --- accuracy --- technical guidelines --- DSM assessment --- backpack mobile mapping --- underground cellars --- unmanned aerial vehicle --- unmanned aerial system --- vision-based navigation --- search and rescue --- vision and action --- OODA --- inspection --- target detection --- autonomous localization --- 3D registration --- GPS-denied environment --- real-time --- multi-robot --- bioinspired map --- topologic mapping --- map exploration --- onboard GNSS RTK --- UAS traffic management --- multiple UAV navigation --- navigation in GPS/GNSS-denied environments --- distributed state estimation --- consensus theory --- computer architecture --- decision making --- navigation --- semantics --- aerial systems --- applications, inspection robotics, bridge inspection with UAS --- POMDP --- Deep Reinforcement-Learning --- multi-agent --- search

Listing 1 - 6 of 6
Sort by


Copyright ©2024 SemperTool