In this research, we propose a unique multi-planar LIDAR and computer vision calibration algorithm. This method only requires the camera and LIDAR to observe a planar pattern at different positions and orientations. Geometric constraints of the dasiaviewspsila from the LIDAR and camera images are resolved as the coordinate transformation coefficients. The proposed approach consists of two stages: solving a closed-form equation, followed by applying a non-linear algorithm based on a maximum likelihood criterion. To the author's best knowledge, this is the first paper for a multi-planar LIDAR and vision system calibration. Compared with the classical methods which use dasiabeam-visiblepsila cameras or 3D LIDAR systems, this approach is easy to implement at low cost. Additionally, computer simulation and real world testing have been carried out to evaluate the performance of this approach. Lastly, application of the technique for automated navigation is presented.