Integrated System for Robust 6-DOF Positioning Utilizing New Closed-Form Visual Motion Estimation Methods in Planar Terrains

Estimating the relative positions and (or) trajectory of a camera from video images is a fundamental problem in motion vision. Of special relevance is the closed-form solution for planar scenes, for processing fly-over imagery from airborne and underwater robotics platforms, automated airplane landing utilizing runway landmarks, photomosaicing, etc. However, the method's robustness can break down in certain scenarios, e.g., due to inherent translation-rotation ambiguity of visual motion with short baselines and narrow field of view. The robustness can be improved by devising methods that compute a smaller set of motion parameters, utilizing other sensors to measure the remaining components. This paper addressed key issues in six degrees of freedom positioning from fly-over imagery by integrating vision with rotational angle sensors. First, we propose and utilize robust closed-form solutions for estimating the motion and orientation of a planar surface from the image flow variations up to first order, given measurements of pitch and roll motions. We also describe a calibration technique to enable the integration of angle sensor and visual measurements. Next, an error analysis enables us to evaluate the impact of inaccurate pitch and roll measurements on the estimates from the new closed-form solutions. Finally, the performance of our new methods and the integrated positioning system are evaluated in various experiments with synthetic and real data