Accurate pose determination for autonomous vehicle navigation
In this paper, the translational accuracy performance of two algorithms that allow the pose of an Unmanned Aerial Vehicle (UAV) to be estimated is reported, based on preliminary data. The two algorithms are the 2D Homography and the 3D Iterative Closest Point (ICP) algorithm. Performance is measured against real image data taken with a digital Nikon D70 camera, with lens set at 3 different focal lengths. It is shown that best accuracy is achieved with the 3D Iterative Closest Point algorithm and that focal length itself has little or no bearing on this performance. Calibration errors may impact accuracy.
|Conference||2013 18th International Conference on Methods and Models in Automation and Robotics, MMAR 2013|
Walker, M.J. (Mark J.), & Sasiadek, J. (2013). Accurate pose determination for autonomous vehicle navigation. Presented at the 2013 18th International Conference on Methods and Models in Automation and Robotics, MMAR 2013.