Stereo vision terrain modeling for non-planar mobile robot mapping and navigation

It is common to limit the robot navigation problem to that of navigating in 2-D environments, representing the world with a single plane. This research proposes a system in which a mobile robot can successfully detect, map and navigate through environments containing ramps, thus overcoming the planar limitation. Stereo depth maps of the environment are integrated into height maps using a Kalman filter approach. The accuracy of these maps allow for the robot´s height, pitch and roll to be estimated as it travels over mapped terrain. Estimated robot attitude can then be used to further integrate stereo vision data.