Correction of Laser Rangefinder Measurement Results Using a Color Sensor

Abstract

This study investigates the enhancement of laser rangefinder (LRF) measurement accuracy by incorporating color sensor (CS) correction. The research focuses on mitigating the influence of surface reflectance properties, such as roughness and moisture, which significantly affect the precision of time-of-flight (ToF)-based LRF measurements. A measurement stand was constructed to conduct experiments on various types of paper with different reflectivity levels. Mathematical models for distance estimation were developed using multiple nonlinear regression analysis, both with and without CS correction. The results demonstrate that the model incorporating CS correction provides more accurate distance predictions compared to the uncorrected model. The optimal polynomial degree for the regression model was determined to be three, and the adequacy of the model was confirmed using Fisher's criterion. The study highlights the importance of CS correction in improving LRF measurement accuracy, particularly in applications requiring high precision, such as industrial automation, robotics, and autonomous systems.