Slam method and Slam device based on prior information

Abstract

The invention provides a Slam method based on prior information. The method includes the steps of: 1) adding an initial pose node, extracting primary feature of initial radar observation, marking keyfeatures, adding a feature node to a map, and calculating the constraint and weight of the feature node and the initial pose node; 2) extending the map by means of observation, the prior information and the key features; 3) when the last frame of radar observation information is added to the map, performing global optimization to obtain a route and a feature map; 4) establishing a raster map of the environment on the basis of a Bayesian filter according to the route, which is obtained through the final optimization, of a movable robot and observation corresponding to every pose. The prior information is introduced through the expandable feature hierarchy, so that the method can adapt different environments and prior information in different types; besides the structural features, the key features are also considered, and the framework and size of the environment are further constrained by means of the extra constraint among the key features, thus reducing accumulated error.

Description

technical field [0001] The invention relates to the field of robot positioning, in particular to a Slam method and device based on prior information. Background technique [0002] In order to enable mobile robots to effectively perform tasks in complex environments, such as handling, rescue, cleaning, etc., the robot needs to have the ability of autonomous positioning. GPS cannot be used in indoor and other scenarios or the accuracy cannot meet the requirements; the odometer also has cumulative errors, so the traditional single sensor cannot determine the pose. Localization based on known maps is considered well-solved, but a priori Figure 1 Therefore, how to recognize the environment and construct a high-precision map when the robot pose cannot be determined is of great significance to the navigation of mobile robots. This problem has been a hot spot in the field of robotics in recent decades. It is called for SLAM. SLAM based on EKF or particle filter can locate and map...

AI Technical Summary

Problems solved by technology

The main disadvantage of this approach is that the constraints between features are not considered, and the known or potential structural information in the environment cannot be utilized.

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