关键词: 单目视觉, 移动机器人, 导航, 避障, 区域生长, 模糊逻辑

Abstract: The combine of machine vision and robotics is a major trend in the future development of the robotics industry. In the schemes of mobile robot obstacle avoidance, there are many problems with using traditional sensors, and the acquired information is limited. So a method of monocular vision-based mobile robot obstacle avoidance and navigation is proposed. And if the camera lens focal length is known, there is no need for camera calibration in the application. To reduce the impact of light on the edge detection of the obstacle, the color image is converted to the HSI space. Detecting the edge of converted components by using canny algorithm, and the test results are synthesized. Filtering synthetic results by thresholding, to remove weak edge information and improve the detection accuracy. Connecting the spurious edges by morphological processing, and non-obstacle area is obtained through regional growth. The mapping between the image coordinate system and the robot coordinate system is established according the geometric relationship. Finally, using fuzzy logic combined with membership functions to obtain robot control parameters. Experimental results show that the image color space conversion reduces the impact of the shadow and reflective of ground surface, the algorithm can effectively eliminate the interference of ground stripes and accurately detect the edge of the obstacle, and fuzzy logic decision method improves the robustness of the algorithm and the reliability of results.

Key words: monocular vision, mobile robot, navigation, obstacle avoidance, regional growth, fuzzy logic