Automatic Docking Recognition and Location Algorithm of Port Oil Loading Arm Based on 3D Laser Point Cloud

In view of the traditional artificial traction oil arm docking low degree of automation, poor safety problem, this paper puts forward a kind of automatic docking visual recognition algorithm for port oil arm based on 3D laser point cloud data. First of all, RANSAC(Random Sample Consensus) algorithm is used for plane segmentation of scattered point cloud data scanned by lidar. For the partitioned plane, Euclidean clustering algorithm is used to obtain the target nozzle plane. Then extracting the feature of each orifice separately to get the centroid coordinates to realize the identification and positioning. The experimental results show that the algorithm can meet the needs of spot flange identification, accurate the positioning, meet the needs of automatic docking of oil loading arm and improve the docking efficiency.