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 5Hz 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 relat...
Cullen Jennings, Don Murray, James J. Little