Cooperative robot localization with vision-based mapping

Two stereo vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. A novel landmark recognition system allows one robot to automatically find suitable landmarks in the environment. The second robot uses these landmarks to localize itself relative to the first robot´s reference frame, even when the current state of the map is incomplete. The robots have a common local reference frame so that they can collaborate on tasks, without having a prior map of the environment. Stereo vision processing and map updates are done at 5 Hz and the robots move at 200 cm/s. Using occupancy grids the robots can robustly explore unstructured and dynamic environments. The map is used for path planning and landmark detection. Landmark detection uses the map´s corner features and least-squares optimization to find the transformation between the robots´ coordinate frames. The results provide very accurate relative localization without requiring highly accurate sensors. Accuracy of better than 2 cm was achieved in experiments