An improved method of ptam based on ground features of intelligent robots

A technology of intelligent robots and robots, applied in the field of robot vision, can solve the problems of camera movement restrictions and the inability to establish metric maps
CN104732518BInactive Publication Date: 2017-09-01BEIJING UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING UNIV OF TECH
Publication Date
2017-09-01
Estimated Expiration
Not applicable · inactive patent

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Abstract

An improved method of PTAM based on the ground features of intelligent robots. First, parameter correction is completed, which includes parameter definition and camera correction; The feature information in the current image establishes the data association between the corner features to obtain the pose estimation model; in the initial drawing stage of the map, two key frames are obtained to set up the camera on the mobile robot; during the initialization process, the mobile robot starts Move, and at the same time, the camera captures the information of the corner points in the current scene and establishes an association; after the initialization of the 3D sparse map, update the key frame and use the epipolar search and block matching method to establish the sub-pixel precision mapping relationship of the feature points, combined with the pose estimation model to achieve Camera precise repositioning. Finally, the matching points are projected into the space to complete the creation of the 3D map of the current global environment.
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Description

technical field

[0001] The invention belongs to the field of robot vision and relates to an improved PTAM algorithm based on ground features. Background technique

[0002] As the relationship between robots and humans is getting closer, the related technologies of intelligent robots have received great attention. Simultaneous Localization and Mapping (SLAM) of mobile robots is one of the most mainstream positioning technologies for intelligent mobile robots. It is actually a motion estimation problem, using the internal and external data acquired by the sensor to calculate the position of the mobile robot at a certain moment, and at the same time establish the map model it depends on. Vision-based SLAM belongs to the research category of visual measurement, because the visual sensor has its own unique advantages: small size, light weight, cheap price, easy installation, and the extracted external information is very rich. These advantages further promote the current resear...

Claims

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