This invention discloses a
lidar loop closure detection method based on hierarchical
frequency domain feature extraction. The method includes: a
robot collecting
point cloud data of the current driving environment using an onboard
lidar sensor during its movement, acquiring original
lidar point clouds, with each lidar frame corresponding to one original
lidar point cloud; dividing the original
lidar point cloud into multiple
layers according to height, and acquiring the
frequency domain signature vectors of the layered sub-point clouds; integrating all
frequency domain signature vectors of the lidar frames to obtain a frequency domain
signature matrix; determining
loop closure constraint factors and correcting the
robot pose based on the frequency domain
signature matrix corresponding to the current lidar frame acquired by the
robot and the frequency domain signature matrices corresponding to the lidar frames to be matched in the historical trajectory; and correcting the robot's motion behavior based on the corrected robot
pose. This invention has the advantages of high
loop closure detection rate, high detection accuracy, strong detection robustness, and strong real-time performance.