The invention discloses a bolt and nut
pose estimation method based on an image and a
point cloud, and the method comprises the steps: carrying out the systematic collection of a bolt and nut image through a mechanical arm, constructing a high-
quality data set, carrying out the training based on a YOLOv8
algorithm, and achieving the quick positioning of a bolt and a nut in a two-dimensional image; secondly, a target in the two-dimensional image is mapped to a three-dimensional
point cloud through a camera internal reference matrix,
point cloud data of the bolt and the nut are segmented, and outliers are removed through
statistical filtering; aiming at the
pose estimation of the bolt, innovatively using an RANSAC three-dimensional
circle fitting algorithm to calculate the circle center and the normal vector of the upper surface of the bolt; for the nut, the plane of the nut is recognized through RANSAC
plane fitting, and the
pose of the nut is obtained in combination with a three-dimensional
circle fitting algorithm; according to the method, the intelligent level and efficiency of
overhead line system maintenance are remarkably improved, the risk and labor intensity of manual maintenance are reduced, and
technical support is provided for intelligent operation and maintenance of electrified railways.