Multiple two-dimensional laser rangefinders (LRFs) are applied in many applications like mobile robotics, autonomous vehicles, and three-dimensional reconstruction. The extrinsic calibration between LRFs is the first step to perform data fusion and practical application. In this paper, we proposed a simple method to calibrate LRFs based on a corner composed of three mutually perpendicular planes. In contrast to other methods that require a special pattern or assistance from other sensors, the trihedron corner needed in this method is common in daily environments. In practice, we can adjust the position of the LRFs to observe the corner until the laser scanning plane intersects with three planes of the corner. Then, we formed a Perspective-Three-Point problem to solve the position and orientation of each LRF at the common corner coordinate system. The method was validated with synthetic and real experiments, showing better performance than existing methods.

The combination of a camera and a 2D laser rangefinder (LRF) is widely used in robotics, mapping, and unmanned driving to simultaneously obtain the 3D geometry and color texture of a scene. However, data misregistration between the camera and the LRF frequently occurs due to the difficulty of precise installation and alignment between them. Extrinsic calibration between the camera and the LRF is necessary. In this study, a photogrammetric control field is used to perform a robust and accurate calibration between the camera and the LRF which requires only one shot. With the use of the photogrammetric control field as the common reference, extrinsic calibration between two sensors is decoupled by calibrating each sensor separately. First, using the room corner of the control field, the LRF is calibrated with respect to the control field by solving a simplified perspective-three-point problem. Then, a large number of control points are used to obtain the robust and accurate extrinsic parameters of the camera with respect to the control field. Experiments with simulated and real data were performed. The experimental results show that the proposed scheme is accurate, precise, and robust under different noise levels, and the calibration results can be utilized in indoor and outdoor applications.

The combination of area-scan camera and 2D laser rangefinder (LRF) can capture both textural and geometrical information from a scene at the same time, and has been widely used in various fields. Due to the differences of the installation position and acquisition mode, calibrating the extrinsic parameters, including the rotation and translation, of two sensors is necessary for fusing the camera image and LRF data. In this paper, a simple and flexible extrinsic calibration method is proposed by only acquiring a checkerboard trihedron once. Using checkerboard trihedron as a mobile referenced control field, the proposed method includes three steps to calibrate the extrinsic parameters. First, the rotation and translation between the trihedron and LRF are solved with a simplified perspective-three-point (P3P) solution; Second, using the collinear equation of checkerboard corners and their pixels in the image, the camera is calibrated with respect to the trihedron; Third, combining the last two steps, the rotation and translation parameters between the camera and LRF are finally calibrated with the intermediate referenced trihedron. After a lot of simulation and real experiments, the proposed method has been demonstrated to have the advantages of simple operation, strong robustness and high accuracy in real experiment.