A Novel Filtering Approach in Visual Odometry for Autonomous Ground Vehicles Application

Abstract

A monocular Visual Odometry system has been developed and tested on different datasets and the outputs have been compared with the available ground truth information to analyze the precision of the system. This system is capable of estimating the 3D position of a ground vehicle robustly and in real time. One of the main challenges of monocular VO is the ambiguity of the scale estimation which is addressed by assuming that the ground is locally planar and the height of the mounted camera from the ground is fi xed and known. In order to improve the VO estimation and to help other stages of VO process an effective fi ltering approach is utilized. It is shown that an IMM fi ltering can address the needs of this speci c application, as the movement of a ground vehicle, is different depending on different scenarios. The results of simulation on the well-known KITTI dataset demonstrates that our system's accuracy improved compared to what is considered to be one of the best state-of-the-art monocular Visual Odometry system.