Stereo Visual Odometry for Urban Vehicles Using Ground Features

Autonomous vehicles rely on the accurate estimation of their pose, speed and direction of travel to perform basic navigation tasks. Although GPSs are very useful, they have some drawbacks in urban applications. Visual odometry is an alternative or complementary method, because it uses a sensor already available in many vehicles for other tasks and provides the ego motion of the vehicle with enough accuracy. In this paper, a new method is proposed that detects and tracks features available on the surface of the ground, due to the texture of the road or street and road markings. This way it is assured only static points are taking into account in order to obtain the relative movement between images. A Kalman filter is used taking into account the Ackermann steering restrictions. Some results in real urban environments are shown in order to demonstrate the good performance of the algorithm.