Raster map building method based on local map splicing

Abstract

The invention discloses a raster map building method based on local map splicing.The method comprises the following steps that 1, a robot scans and records environment information; 2, scanning data points are filtered to remove useless points; 3, local raster maps are calculated based on the filtered data through a ray tracking method; 4, sift feature points and corresponding feature descriptors of the local raster maps under two adjacent poses are calculated; 5, according to relevancy of the feature descriptors, the feature points are ranked, and feature points with small feather feature descriptors are filtered away; 6, the two local maps are subjected to iterative closest point algorithm ICP, and a transformation matrix of the two local maps is calculated; 7, the steps 1-6 are repeated, a transformation matrix of the whole path is recorded and completed, and finally data is merged to obtain a global raster map.The map is built through one-time laser data, so that the estimation error of the map is mainly the observation error of a laser sensor, and no estimation error exits.

Description

technical field [0001] The invention belongs to the technical field of map creation, and in particular relates to a grid map creation method based on partial map splicing. Background technique [0002] There are four representation methods of maps in robotics: feature maps, topological maps, grid maps, and direct representation methods (AppearanceBasedMethods). Feature maps represent the environment with related geometric features (such as points, lines, surfaces). The topological map represents the indoor environment as a topological structure diagram with nodes and related connecting lines, where the nodes represent important points in the environment (corners, doors, elevators, stairs, etc.), and the edges represent the connection relationship between nodes, such as hallway etc. A grid map divides the environment into a series of grids, where each grid is given a possible value, indicating the probability that the grid is occupied. The direct representation method omit...

AI Technical Summary

Problems solved by technology

[0003] The existing raster representation requires sensors such as encoders and IMUs when used, and the method of using internal sensor information to accumulate estimated mileage information and then construct a map is not accurate enough because internal sensor errors will continue to accumulate; at the same time, the traditional method is due to the need Simultaneously process all observation data on the entire path, so its operating efficiency decreases significantly as the map scale increases, and it is difficult to apply to large-scale environmental map construction

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