Mobile remote sensing platform: An uncertainty calibration analysis

This paper presents a method to estimate the uncertainty in the calibration of two sensors, a laser rangefinder and a multicamera-system. Both sensors were used in urban environment reconstruction tasks. A new calibration pattern, visible to both sensors is proposed. By this means, correspondence between each laser point and its position in the camera image is obtained so that texture and color of each LIDAR point can be known. Besides this allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. A practical methodology is presented to predict the uncertainty analysis inside the calibration process between both sensors. Statistics of the behavior of the camera calibration parameters and the relationship between the camera, LIDAR and the noisy of both sensors were calculated using simulations, an analytical analysis and experiments. Results for the calibration and uncertainty analysis are presented for data collected by the platform integrated with a LIDAR and the panoramic camera.