This paper describes an image based visual servoing (IBVS) system for a
nonholonomic robot to achieve good trajectory following without real-time robot
pose information and without a known visual map of the environment. We call it
trajectory servoing. The critical component is a feature-based, indirect SLAM
method to provide a pool of available features with estimated depth, so that
they may be propagated forward in time to generate image feature trajectories
for visual servoing. Short and long distance experiments show the benefits of
trajectory servoing for navigating unknown areas without absolute positioning.
Trajectory servoing is shown to be more accurate than pose-based feedback when
both rely on the same underlying SLAM system