TY - GEN
T1 - A neural network based omni light sensor
AU - Medina, Oded
AU - Yozevitch, Roi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/4
Y1 - 2017/8/4
N2 - The usage of optical distance-sensors is common in robotics research. These are usually based on photoresistors, photo-transistors or photo-diodes. This paper presents a novel design for a passive sensor configured as a 18 photo-resistors array. The device is designed to locate a light source in R3. In order to simplify the wiring task, we connect all photo-resistors to each other as the edges of an octahedron with an additional center node configuration. We then wire the peripheral pins to analog-digital-converters. The resulting resistance distribution is then analyzed using a dedicated neural network. We present the experimental process, its results and the sensor's accuracy.
AB - The usage of optical distance-sensors is common in robotics research. These are usually based on photoresistors, photo-transistors or photo-diodes. This paper presents a novel design for a passive sensor configured as a 18 photo-resistors array. The device is designed to locate a light source in R3. In order to simplify the wiring task, we connect all photo-resistors to each other as the edges of an octahedron with an additional center node configuration. We then wire the peripheral pins to analog-digital-converters. The resulting resistance distribution is then analyzed using a dedicated neural network. We present the experimental process, its results and the sensor's accuracy.
UR - https://www.scopus.com/pages/publications/85029896853
U2 - 10.1109/ICCA.2017.8003175
DO - 10.1109/ICCA.2017.8003175
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AN - SCOPUS:85029896853
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 872
EP - 875
BT - 2017 13th IEEE International Conference on Control and Automation, ICCA 2017
PB - IEEE Computer Society
T2 - 13th IEEE International Conference on Control and Automation, ICCA 2017
Y2 - 3 July 2017 through 6 July 2017
ER -