A slam method for closed-loop detection of orb keyframes that can improve robot pose consistency

Abstract

The invention discloses an ORB key frame closed-loop detection SLAM method capable of improving the consistency of the position and the pose of a robot. The ORB key frame closed-loop detection SLAM method comprises the following steps of, firstly, acquiring color information and depth information of the environment by adopting an RGB-D sensor, and extracting the image features by using the ORB features; then, estimating the position and the pose of the robot by an algorithm based on RANSAC-ICP interframe registration, and constructing an initial position and pose graph; and finally, constructing BoVW (bag of visual words) by extracting the ORB features in a Key Frame, carrying out similarity comparison on the current key frame and words in the BoVW to realize closed-loop key frame detection, adding constraint of the position and pose graph through key frame interframe registration detection, and obtaining the global optimal position and pose of the robot. The invention provides the ORB key frame closed-loop detection SLAM method with capability of improving the consistency of the position and the pose of the robot, higher constructing quality of an environmental map and high optimization efficiency.

Description

technical field [0001] The invention relates to the field of Simultaneously Localization and Mapping (SLAM) of a robot, in particular to an ORB key frame closed-loop detection SLAM method that can improve the pose consistency of a robot. Background technique [0002] In order to realize autonomous movement and navigation in an unknown indoor environment, the intelligent robot should have the ability to build an indoor environment map and at the same time have the ability to locate in the global map. The above process is also called Simultaneously Localization and Mapping , SLAM). When the robot is in an outdoor environment, the positioning under the global map can be realized through high-precision GPS and prior maps. However, when the robot is in an indoor environment, or in an environment where GPS is not available (underwater, mines), other methods must be adopted to achieve robot SLAM. [0003] The existing indoor SLAM methods have shortcomings: poor positioning consis...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the disadvantages of poor positioning consistency between existing indoor robot positioning and environmental map construction, low quality of environmental map construction, and low optimization efficiency, the present invention provides a robot that can improve the consistency of robot pose, high quality of environmental map construction, and optimization. Efficient SLAM method for ORB key frame closed-loop detection

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