부산대학교 도서관

Laser range finders are used in industrial safety and surveillance applications, e.g. to track persons. The relative position between two sensors is needed for the correct operation of such a system. In order to reduce costs, sensors are positioned to have minimal overlap while extending the combined field of view. The necessary calibration is often done in a time-consuming manual process. To automate this, moving objects are tracked in the laser scans and used to find the relative sensor poses. We present a novel approach to pairwise calibration using shared observations in a RANSAC-based fashion to estimate the relative transformation between two sensors. Afterwards, we apply robust pose graph optimization that deals with possibly faulty pairwise estimates. Our method uses ℓ 1 -norm minimization in the tangential space of the rotation matrices under transitivity constraints and, thus, does not need a further initial guess to obtain the final sensor poses. The complete system is evaluated with simulated and real data in very challenging situations. To emphasize the robustness of the proposed calibration, we show results using a very simple non-robust tracking. The overall accuracy is further improved when ellipse fitting of the tracked targets is used.