Open AccessAutonomous Obstacle Avoidance Scheme Using Monocular Vision Applied to Mobile Robots
Author(s) -
Yun Yun Song,
Yang Su,
Chao Liu,
Qing Gui Wu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012024
Subject(s) - computer vision , artificial intelligence , obstacle avoidance , obstacle , monocular , mobile robot , computer science , monocular vision , scheme (mathematics) , robot , feature (linguistics) , position (finance) , collision avoidance , pixel , mathematics , geography , computer security , mathematical analysis , linguistics , philosophy , archaeology , finance , collision , economics
Mobile robots cannot move in an unknown environment with static or slow-moving obstacles effectively. We present an enhanced obstacle avoidance strategy using monocular vision to solve this problem. First, we combine Canny and Otsu to extract the barrier feature and find the critical pixel position of obstacles by the monocular vision. Then the image depth estimation algorithm is used to estimate the gaps. With these parameters of barriers, an improved bug algorithm is proposed to avoid the obstacles autonomously. The experiments show that the proposed obstacles avoidance strategy can effectively make a small mobile robot avoid different kinds of obstacles.