J-ISPIN has awarded the winners of the IPIN conference with the best paper award and looks forward to publishing their papers in the IEEE open access journal shortly.
October 18, 2023
Twentythree ultra-wideband anchors collaborate to calibrate themselves in challenging industrial conditions with limited connectivity. The algorithm is able to localize the anchors with an mean absolute error of only 21.6 cm.
Necessity of environment detection in a seamless localization scenario, where the mobile object moves in different environments and uses various positioning methods. For example:
1) crowded urban area, where (s)he uses 5G signals for positioning,
2) indoor building, where (s)he utilizes camera and map-based method for localization,
3) open area, where the pedestrian deploys GNSS receivers to locate itself.
AI improves wearable inertial device-based pedestrian navigation. This paper classifies these AI methods into two categories based on signal segmentation methods: human gait and sampling frequency-driven. To complete the analysis, SELDA (category 1), RONIN (category 2) and a non-AI gait-driven method SmartWalk were evaluated in a 2,17 km long open access dataset, representative of the diversity of pedestrians’ mobility surroundings.
Univ. Gustave Eiffel
Bouguenais, France
ISTI-CNR
Pisa, Italy
ISTI-CNR
Pisa, Italy
ISTI-CNR
Pisa, Italy
Univ. Gustave Eiffel
Versailles, France
University of Connecticut
United States
University of Haifa
Israel
Tampere University
Tampere, Finland
Sapienza Università di Roma
Roma, Italy
University of Calgary
Calgary, AB, Canada
Washington University St. Louis
Missouri, USA
Shanghai Jiao Tong University
Shanghai, China
Linköping University
Linköping, Sweden
Universidade do Minho
Guimarães, Portugal
Hokkaido University
Sapporo, Japan
University at Oxford
Oxford, United Kingdom
University of Alcalá
Madrid, Spain
AIR Chinese Academy of Sciences (CAS)
Beijing, China
Shenzhen University
Shenzhen, China
