Mapping and positioning method based on sensor information fusion

Abstract

The invention relates to a mapping and positioning method based on information fusion, comprising the following steps: A. obtaining information of a robot body and surrounding environment by a sensor;B. processing data, and simultaneously creating a local map and performing feature matching to construct a global map; C. fusing data measured by an odometer and an IMU (Inertial Measurement Unit) byadopting a filtering algorithm to generate new pose information of a robot; at the same time, fusing environmental features acquired by a Kinect and a 2D laser radar based on a Bayesian algorithm toobtain new feature information; and finally, constructing a new local map based on the new environmental feature information and the new pose information; and D. performing feature matching on the newlocal map and the global map to complete data association, updating the global map by using the new local map, and outputting the global map. According to the mapping and positioning method of the invention, a raster map constructed based on the sensor information fusion is added with the environmental feature information, so that obstacles in a three-dimensional space can be detected; and meanwhile, the positioning precision is improved after fusion and complementation of the data of the odometer and the IMU.

Description

technical field [0001] The invention belongs to the field of path planning of a mobile robot, in particular to a method for constructing a grid map and positioning based on sensor information fusion. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Today's mobile robots are involved in all walks of life, and have been widely used in home services, industrial manufacturing, special operations, and military operations. One of the core technologies used by mobile robots in these fields for path planning is map construction and positioning. [0004] SLAM (Synchronous Localization and Map Construction) is a key step in path planning, which will directly affect the result of obstacle avoidance. At present, there are still a series of problems in path planning based on SLAM of a certain sensor alone; 2D lidar can only obtain two-dimensional Plan...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that a single sensor has some shortcomings in mapping and positioning in the background technology and thus affect the obstacle avoidance of the robot, the present invention provides a mapping and positioning method based on sensor information fusion, which specifically includes the following steps:

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