Indoor Positioning and Navigation

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 i...

Full description

Saved in:
Bibliographic Details
Other Authors: Tomažič, Simon (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
UAV
GPS
n/a
Online Access:DOAB: download the publication
DOAB: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000naaaa2200000uu 4500
001 doab_20_500_12854_76846
005 20220111
003 oapen
006 m o d
007 cr|mn|---annan
008 20220111s2021 xx |||||o ||| 0|eng d
020 |a books978-3-0365-1912-8 
020 |a 9783036519135 
020 |a 9783036519128 
040 |a oapen  |c oapen 
024 7 |a 10.3390/books978-3-0365-1912-8  |c doi 
041 0 |a eng 
042 |a dc 
072 7 |a TB  |2 bicssc 
072 7 |a KNB  |2 bicssc 
100 1 |a Tomažič, Simon  |4 edt 
700 1 |a Tomažič, Simon  |4 oth 
245 1 0 |a Indoor Positioning and Navigation 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (350 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
650 7 |a Energy industries & utilities  |2 bicssc 
653 |a dynamic objects identification and localization 
653 |a laser cluster 
653 |a radial velocity similarity 
653 |a Pearson correlation coefficient 
653 |a particle filter 
653 |a trilateral indoor positioning 
653 |a RSSI filter 
653 |a RSSI classification 
653 |a stability 
653 |a accuracy 
653 |a inertial navigation system 
653 |a artificial neural network 
653 |a motion tracking 
653 |a sensor fusion 
653 |a indoor navigation system 
653 |a indoor positioning 
653 |a indoor navigation 
653 |a radiating cable 
653 |a leaky feeder 
653 |a augmented reality 
653 |a Bluetooth 
653 |a indoor positioning system 
653 |a smart hospital 
653 |a indoor 
653 |a positioning 
653 |a visually impaired 
653 |a deep learning 
653 |a multi-layered perceptron 
653 |a inertial sensor 
653 |a smartphone 
653 |a multi-variational message passing (M-VMP) 
653 |a factor graph (FG) 
653 |a second-order Taylor expansion 
653 |a cooperative localization 
653 |a joint estimation of position and clock 
653 |a RTLS 
653 |a indoor positioning system (IPS) 
653 |a position data 
653 |a industry 4.0 
653 |a traceability 
653 |a product tracking 
653 |a fingerprinting localization 
653 |a Bluetooth low energy 
653 |a Wi-Fi 
653 |a performance metrics 
653 |a positioning algorithms 
653 |a location source optimization 
653 |a fuzzy comprehensive evaluation 
653 |a DCPCRLB 
653 |a UAV 
653 |a unmanned aerial vehicles 
653 |a NWPS 
653 |a indoor positioning systems 
653 |a GPS denied 
653 |a GNSS denied 
653 |a autonomous vehicles 
653 |a visible light positioning 
653 |a mobile robot 
653 |a calibration 
653 |a appearance-based localization 
653 |a computer vision 
653 |a Gaussian processes 
653 |a manifold learning 
653 |a robot vision systems 
653 |a image manifold 
653 |a descriptor manifold 
653 |a indoor fingerprinting localization 
653 |a Gaussian filter 
653 |a Kalman filter 
653 |a received signal strength indicator 
653 |a channel state information 
653 |a indoor localization 
653 |a visual-inertial SLAM 
653 |a constrained optimization 
653 |a path loss model 
653 |a particle swarm optimization 
653 |a beacon 
653 |a absolute position system 
653 |a cooperative algorithm 
653 |a intercepting vehicles 
653 |a robot framework 
653 |a UWB sensors 
653 |a Internet of Things (IoT) 
653 |a wireless sensor network (WSN) 
653 |a switched-beam antenna 
653 |a electronically steerable parasitic array radiator (ESPAR) antenna 
653 |a received signal strength (RSS) 
653 |a fingerprinting 
653 |a down-conversion 
653 |a GPS 
653 |a navigation 
653 |a RF repeaters 
653 |a up-conversion 
653 |a n/a 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/4295  |7 0  |z DOAB: download the publication 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/76846  |7 0  |z DOAB: description of the publication