Obstacle feature point detection method for real-time processing by monocular camera and line laser

In this study, we propose a method for detecting feature points of obstacles by real-time processing using a monocular camera and a laser. Specifically, we propose an algorithm that detects laser beams emitted on obstacles by binarization, transforms pixel coordinates into distance using triangulation by a laser beam that is obliquely incident on the ground, and estimates the placement angle of the obstacle in real-time processing. No method has been devised to detect the placement angle of obstacles using a monocular camera and a laser. Furthermore, the proposed method does not calculate the linear distance from the camera, but from the position where the camera is moved horizontally parallel to the obstacle in front of the camera, thus detecting the placement angle independently of the placement position of the obstacle. As a result, it was confirmed that the placement angles of obstacles could be detected with a maximum error of \(6^{\circ }\) $6^{\circ }$ in six placement positions. Therefore, we succeeded in automatically detecting the placement angle of obstacles in real-time, independent of the illumination of the measurement environment, the reflectance of the obstacle.