In this chapter we discuss the calibration of a rotating panoramic sensor (rotating sensor-line camera or laser range-finder). Having specified some preprocessing steps, we describe a least-squares error method which implements the point-based calibration technique (common in photogrammetry or computer vision, using projections of control points, also called calibration marks). This method has been used frequently in applications, and proved to be robust and accurate.
The chapter also discusses three calibration methods at a more theoretical level, for comparing calibration techniques for the general multi-center panorama case.1 The aim of this discussion is to characterize the linear and non-linear components in the whole calibration process.
As pointed out at the end of Chapter 3, the geometry of the LRF can be understood (for calibration purposes) as a special case of the geometry of the rotating sensor-line camera. Therefore we prefer to use camera notation in this chapter. However, a section at the end of the chapter also discusses the specific errors to be considered for a laser range-finder.
Calibration of panoramic sensors builds on traditional camera calibration techniques (e.g., in computer vision or photogrammetry). This section briefly introduces the subject, and provides a few general definitions.
5.1.1 Camera Calibration
Photogrammetry or computer vision uses calibration marks, which are typically intersection points of lines, or of ...