A study of omni-directional image based environment recognition for mobile robots

The development of intelligent autonomous mobile robots is an area of active research. To develop intelligent autonomous mobile robots, it is necessary to select appropriate sensing devices and a robust environment recognition algorithm. To achieve robust and stable navigation for mobile robots, we employ an omni-directional camera, which is a suitable image capturing device for mobile robots because it can capture images of the surrounding environment without a dead angle. In order to recognize the surrounding environment from captured images, we newly developed an environment recognition algorithm that is suitable for omni-directional images. From the results of environment recognition, the robot can find an appropriate path for navigation. The features of the new algorithm are as follows: (1) Morphological operations are applied to detect obstacles robustly and accurately; (2) A quad-tree region segmentation based lane detection algorithm is applied; and (3) An improved Hough transform which can detect curved lanes is used to confirm the results of (2). The effectiveness of the new algorithm was confirmed.