Year: 2025
Type: conference-paper
Abstract: Infrared (IR) proximity sensors measure distance using either time-of-flight (ToF) or reflection intensity methods.While the ToF offers greater precision, it requires costly, specialized components.Reflection-based sensors use simpler circuits, enabling lower-cost designs.This study presents a multi-emitter reflection intensity IR sensor as an economic alternative to near-field object positioning.Six IR LEDs, sequentially driven, surround a central photodiode that captures backscattered signals.A machine learning pipeline estimates the object coordinates, cross-section, and height.Tested on 20 objects and 13,750 labeled data points, the system achieved a <1 cm mean positioning error, which is competitive with multi-zone ToF accuracy with a reduced cost.
Author: Eren Bülbül
Institution: Istanbul Technical University
Language: English
Subfield: Instrumentation
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7122738405