TY - JOUR
T1 - LEDPOS
T2 - Indoor Visible Light Positioning based on LED as Sensor and Machine Learning
AU - Fragner, Christian
AU - Krutzler, Christian
AU - Weiss, Andreas Peter
AU - Leitgeb, Erich
N1 - Publisher Copyright:
Authors
PY - 2024
Y1 - 2024
N2 - Accurate indoor positioning is becoming increasingly important, especially in highly automated industrial environments with robots. In addition, LED-based lighting is also being used more and more frequently in such application fields. In the present work, the possibility to exploit the LED lighting infrastructure with a novel approach for implementing an accurate indoor positioning system is investigated. For this purpose, a demonstrator luminaire LEDPOS is proposed and evaluated that combines visible light sensing based on backscattered reflections to accurately estimate the two-dimensional position of a retroreflective foil at the floor while providing simultaneously an unimpaired room illumination. In particular, the same LED elements are shared for illumination and for the sensing functionality. Furthermore, the algorithm for data evaluation and position determination is based on a machine learning approach that is implemented on the edge in the luminaire. Thus, the presented approach allows for a simple and cost-efficient implementation in different applications. The experimental characterization of the LEDPOS demonstrator in a real-world scenario shows that a very good positioning accuracy can be achieved, in which the average error for the two-dimensional position of the retroreflective foil within an area of 0.64 m2 remains in the range of 3 cm.
AB - Accurate indoor positioning is becoming increasingly important, especially in highly automated industrial environments with robots. In addition, LED-based lighting is also being used more and more frequently in such application fields. In the present work, the possibility to exploit the LED lighting infrastructure with a novel approach for implementing an accurate indoor positioning system is investigated. For this purpose, a demonstrator luminaire LEDPOS is proposed and evaluated that combines visible light sensing based on backscattered reflections to accurately estimate the two-dimensional position of a retroreflective foil at the floor while providing simultaneously an unimpaired room illumination. In particular, the same LED elements are shared for illumination and for the sensing functionality. Furthermore, the algorithm for data evaluation and position determination is based on a machine learning approach that is implemented on the edge in the luminaire. Thus, the presented approach allows for a simple and cost-efficient implementation in different applications. The experimental characterization of the LEDPOS demonstrator in a real-world scenario shows that a very good positioning accuracy can be achieved, in which the average error for the two-dimensional position of the retroreflective foil within an area of 0.64 m2 remains in the range of 3 cm.
KW - Indoor communication
KW - Indoor Positioning
KW - LED as Sensor
KW - Light emitting diodes
KW - Lighting
KW - Machine Learning
KW - Machine learning
KW - Photodiodes
KW - Position measurement
KW - Robot sensing systems
KW - Sensors
KW - Visible light communication
KW - Visible Light Positioning
KW - Visible Light Sensing
KW - LED as sensor
KW - machine learning
KW - visible light positioning
KW - Indoor positioning
KW - visible light sensing
UR - http://www.scopus.com/inward/record.url?scp=85189140930&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2024.3382757
DO - 10.1109/ACCESS.2024.3382757
M3 - Article
AN - SCOPUS:85189140930
SN - 2169-3536
VL - 12
SP - 46444
EP - 46461
JO - IEEE Access
JF - IEEE Access
ER -