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We address the problem of camera-to-laser-scanner calibration using acheckerboard and multiple image-laser scan pairs. Distinguishing which laserpoints measure the checkerboard and which lie on the background is essential toany such system. We formulate the checkerboard extraction as a combinatorialoptimization problem with a clear cut objective function. We propose abranch-and-bound technique that deterministically and globally optimizes theobjective. Unlike what is available in the literature, the proposed method isnot heuristic and does not require assumptions such as constraints on thebackground or relying on discontinuity of the range measurements to partitionthe data into line segments. The proposed approach is generic and can beapplied to both 3D or 2D laser scanners as well as the cases where multiplecheckerboards are present. We demonstrate the effectiveness of the proposedapproach by providing numerical simulations as well as experimental results.

A Branch-and-Bound Algorithm for Checkerboard Extraction in Camera-Laser Calibration