Automated calibration data collection in LRF/camera calibration with online feedback

This work aims to reduce the time used in the data collection phase of the LRF/Camera calibration problem. We propose a framework that partially automates the triggering and identification of calibration data acquisition from a moving calibration object. The automated process uses quality metrics that measure properties of the calibration object that directly affect the accuracy of the calibration. The framework also proposes feedback of these metrics to the human operator. The framework is implemented and numerical example are given. The result shows that our framework can reduce the time used in calibration with adjustable tradeoff between accuracy and data collection time.