Dynamic obstacle point cloud filtering method and device

Abstract

The present application discloses a method for filtering out dynamic obstacle point clouds, comprising: obtaining a frame image and inertial measurement data containing a target area; obtaining second point cloud data and the pose information of the frame image using an iterative error Kalman filter algorithm; obtaining third point cloud data in a global coordinate system using a registration algorithm; dividing the spatial range covered by the third point cloud data into grid cells, and counting the number of point clouds and the point cloud height variance in each grid cell; determining a dynamic grid if the number of point clouds exceeds a first threshold and the absolute value of the variance difference between the number of point clouds and the number of historical frame point clouds exceeds a second threshold; re-marking the dynamic grid as a static grid if the dynamic confidence is lower than a set threshold; obtaining a point cloud of dynamic obstacles using a spatial region growing algorithm, and filtering out the point cloud of dynamic obstacles to obtain static point cloud data of the target area. The present application achieves effective filtering of dynamic obstacle point clouds.

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