Topological map node generation method based on laser point cloud distribution characteristics

Abstract

The invention provides a topological map node generation method based on laser point cloud distribution characteristics, and belongs to the technical field of robots. According to the invention, the method comprises the steps: acquiring three-dimensional point cloud data of a scene by using a three-dimensional laser sensor, dividing the three-dimensional point cloud data into two parts of ground point cloud and non-ground point cloud, and performing outlier elimination and clustering processing on the non-ground point cloud data so as to acquire the number of point cloud categories; performingfeasible region extraction on the ground point cloud, and performing straight line fitting on the extracted feasible region boundary so as to judge whether the current position is a corner or an intersection. A cost function is constructed according to the size of the environment range described by the acquired three-dimensional point cloud data, the number of non-ground point cloud categories, whether the current position is a corner or an intersection or not and the distance between the current position and the previous node, and meanwhile, whether the current position of the robot can generate a topological node or not is judged according to the cost value.

Description

technical field [0001] The invention belongs to the technical field of robots, and in particular relates to a method for generating topological map nodes based on distribution characteristics of three-dimensional laser point clouds. Background technique [0002] Commonly used sensors in the field of mobile robots include 3D lasers, cameras, IMUs, etc. Compared with cameras, 3D lasers are not easily affected by light, and the measurement results are accurate and reliable, so they are widely used in the field of robotics. Due to the high scanning resolution and scanning frequency of 3D lasers, the data volume of laser point clouds accumulated and acquired by mobile robots is increasing, which has a large computational burden. [0003] In the task of mobile robot map construction, the commonly used map representation forms are metric map and topological map. The metric map uses geometric features such as raw data and edges to describe the environment. However, as the scope of t...

AI Technical Summary

Problems solved by technology

Although this method can set important locations such as corners and intersections in the environment as topological nodes, the vision sensor used in this solution is greatly affected by light and cannot work at night. In addition, the measurement range is limited and cannot meet the needs of large-scale outdoor scenarios. Requirements for topological map construction

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