Autonomous Self-Localization of Mobile Robots through Reference Point Based Computer Vision

This paper demonstrates a method for global localization of autonomous mobile robots based on the creation of visual memory maps, through detection and description of reference points from captured images, associated to odometer data in a specific environment. The proposed procedure, coupled with specific knowledge of the environment, allows for localization to be achieved through the pairing of these memorized features with the scene being observed in real time. Experiments are conducted to show the effectiveness of the proposed method for the localization of mobile robots in indoor environments. The results are analyzed and navigation alternatives and possible future refinements are discussed.