Automatic calibration of laser range cameras using arbitrary planar surfaces

摘要

Laser Range Cameras (LRCs) are powerful tools for many robotic /computer perception activities. They can provide accurate range images and perfectly registered reflectance images of the target scene, useful for constructing reliably detailed 3-D world maps and target characterizations. An LRC's output is an array of distances obtained by scanning a laser over the scene. To accurately interpret this data, the angular definition of each pixel, i.e., the 3-D direction corresponding to each distance measurement, must be known. This angular definition is a function of the camera's intrinsic design and unique implementation characteristics, e.g., actual mirror positions, axes of rotation, angular velocities, etc. Typically, the range data is converted to Cartesian coordinates by calibration-parameterized, non-linear transformation equations. Unfortunately, typical LRC calibration techniques are manual, intensive, and inaccurate. Common techniques involve imaging carefully orchestrated artificial targets and manually measuring actual distances and relative angles to infer the correct calibration parameter values. This paper presents an automated method which uses Genetic Algorithms to search for calibration parameter values and possible transformation equations which combine to maximize the planarity of user-specified sub-regions of the image(s). This method permits calibration to be based on an arbitrary plane, without precise knowledge of the LRC's mechanical precision, intrinsic design, or its relative positioning to the target. Furthermore, this method permits rapid, remote, and on-line recalibration - important capabilities for many robotic systems. Empirical validation of this system has been performed using two different LRC systems and has led to significant improvement in image accuracy while reducing the calibration time by orders of magnitude.