Auto-calibration method to determine camera pose for stereovision-based off-road vehicle navigation

Abstract

Stereo cameras have been used as perception sensors for agricultural vehicle navigation for years. One problem impeding their broader application is the difficulty of calibrating the installation poses of a camera using conventional measuring tools, especially when such a system is used in ill-structured agricultural field environments. The research reported in this paper was aimed to develop an automated calibration method for determining the camera installation pose with respect to a vehicle frame. Based on this method, a binocular stereo camera acquired a sequence of field scenery images as the vehicle moved straight forward for a short distance on a relatively flat surface. An image processing algorithm has been developed to detect some static feature points in the ground image and track their three-dimensional (3D) relative motions with respect to the moving vehicle. A plane best fitting to those detected ground features was then used to determine the camera roll and pitch angles, and the tracked motions of those feature points were used to estimate the camera yaw. Field test results validated that the developed autocalibration method was capable of determining the camera installation pose at a calibration accuracy of ±1° over an approximately 10 m of vehicle traveling distance. The calibrated poses could be used to compensate for the navigation errors induced by camera misalignment.