Vision-based fuzzy navigation of mobile robots in grassland environments

In this paper a vision-based algorithm for mobile robot navigation in unknown outdoor environments is proposed. It is based on a simple phenomenon, that when the robot moves forward, projected images of the near obstacles grow in captured frames faster than that of the far objects. The proposed algorithm takes advantage of this property and extracts features from each grabbed frame of the camera and tracks the vertical position of the features and their speed along the Y axis of the image plane over multiple frames as the robot moves. The relative height of the features and their distance from the robot in 3D is inferred based on this data and they are fed into a fuzzy reasoning system which marks the features from safe to unsafe according to their suitability for navigation. Then a second fuzzy system summarizes these scores in different image regions and directs the robot toward the area containing more features marked as safe. Simulation and implementation results confirm the efficacy of the proposed simple algorithm for mobile robot navigation in outdoor environments.