Lidar Odometry Key Frame Selection Based on Displacement Vector Similarity

In order to improve the efficiency and reduce the cumulative error of lidar odometry caused by key frame update. This paper proposes a key frame selection method based on displacement vector similarity. First, calculate the pose between the current frame and the reference key frame according to the Normal Distribution Transform (NDT) algorithm; then, set the Manhattan distance between the two frames above, and calculate the cosine similarity of the displacement vector; finally, update the key frame according to the similarity threshold. The experimental results show that the key frame selection method proposed in this paper can effectively improve the key frame update efficiency and reduce the cumulative error of the odometry: compared with the NDT method updating key frame based on the distance, the maximum absolute error is reduced by 11.88 meters, and the relative error is reduced by 8%,time consumption has been reduced by 55 seconds.