LiDAR Odometry Positioning Method for Degenerate Environment
Simultaneous Localization and Mapping (SLAM) based on Light Detection and Ranging (LiDAR) is one of the core technologies widely used in the field of indoor and outdoor integrated positioning and spatial data acquisition.It has the advantage of strong anti-interference without considering light conditions.However,in degenerate environments lacking geometric features,the traditional LiDAR odometry based on feature registration algorithm or Iterative Closest Point (ICP) algorithm usually produce inaccurate results.To address the above problem,this paper proposes a LiDAR odometer positioning method for degenerate environments using modified laser intensity and an accurate LiDAR degenerate environment detection method.Firstly,an intensity correction method is proposed based on laser intensity properties and the elimination idea,and an unsupervised position correction method is used to jointly optimize the original point cloud.Based on this,four point cloud features are extracted,and the fuzzy comprehensive evaluation method is used to accurately detect the degradation of each frame point cloud.For well-conditioned point clouds,line and surface features are extracted to construct the interest point set.For degenerate point clouds,a " MI word search " method is proposed to extract well-conditioned features based on laser intensity,and the interest point set is constructed with effective line and surface features.Finally,the robust LiDAR odometry is constructed by processing the inter-frame interest point sets through suitable registration algorithms.The experimental results show that the correct rate of laser intensity correction is 93.34％.The correct detection rate of LiDAR degenerate point cloud is 98.58％,and the error detection rate of well-conditioned point cloud is only 2.24％.Compared with the LiDAR odometry based on feature registration algorithm and ICP algorithm,the positioning Root Mean Square Error (RMSE) of the LiDAR odometry positioning method proposed in this paper is reduced by 90.00％ and 83.96％,respectively,and the Maximum Error (MAXE) is reduced by 86.23％ and 79.07％,respectively.The time required for single inter-frame registration is 0.0069 s,which effectively improves the positioning accuracy of traditional LiDAR odometry in degenerate environment while maintaining data processing efficiency.Compared with the other methods in the same field,our method shows more significant advantages.In addition,since the method in this paper is completely innovated and improved on the basis of traditional LiDAR odometer,it has a low overall complexity and significant advantages in terms of secondary development and portability.
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