Real-world clicker calibration with machine learning

Abstract

This paper discusses how to calibrate our developed real-world clicker using machine learning technologies. Our real-world clicker is a system that can measure the 3D coordinate value of a laser spot. A TOF type laser distance sensor is mounted on a pan tilt actuator in which the 3D coordinate value can be calculated from the pan angle and the tilt angle and the laser beam length. Inherently the measurement accuracy is reduced due to assembly error of the actuator and the laser sensor. We propose a method to correct the error by calibration using machine learning.