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Visual SLAM positioning method and device fusing MSCKF and graph optimization

A positioning method and graph optimization technology, which are applied in measurement devices, image enhancement, image data processing, etc., can solve the problem of not being able to guarantee operation efficiency and operation accuracy at the same time, and achieve the effect of ensuring accuracy and efficiency.

Pending Publication Date: 2021-10-19
BEIJING HUAJIE IMI TECH CO LTD
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  • Application Information

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Problems solved by technology

[0005] Based on the deficiencies of the above-mentioned existing technologies, this application provides a visual SLAM positioning method and device that integrates MSCKF and graph optimization to solve the problem that the calculation efficiency and calculation accuracy cannot be guaranteed at the same time in the prior art

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  • Visual SLAM positioning method and device fusing MSCKF and graph optimization
  • Visual SLAM positioning method and device fusing MSCKF and graph optimization
  • Visual SLAM positioning method and device fusing MSCKF and graph optimization

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Embodiment Construction

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0064] In this application, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any relationship between these entities or operations. an actual relationship or order. Moreover, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elem...

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Abstract

The invention discloses a visual SLAM positioning method and device fusing MSCKF and graph optimization. The method mainly comprises the steps of obtaining a current image and inertial data in real time, carrying out the tracking of a plurality of feature points on the current image based on the current inertial data, inputting the information of the plurality of feature points and the inertial data into a filter, carrying out filter prediction and updating, and outputting the current pose, the information of key frames and the information of the plurality of feature points; extracting a target key frame from the key frame queue, processing the key frame, and performing loopback detection on the target key frame; if the loopback detection fails, updating a plurality of map points, the target key frame and the common-view relationship thereof into a map library; and if the loopback detection is successful, performing global optimization on the key frame pose and the map points by using a global beam adjustment method, feeding back an optimization result to the MSCKF for state fusion, and updating the key frame pose and the map points in a sliding window.

Description

technical field [0001] This application relates to the technical field of simultaneous positioning and map construction, in particular to a visual SLAM positioning method and device that integrates MSCKF and graph optimization. Background technique [0002] At present, there are mainly two ways to realize simultaneous localization and mapping (SLAM), which are divided into: a method based on a filtering algorithm and a method based on a nonlinear optimization. [0003] The method based on filtering algorithm is mainly based on the observation information on the newly acquired multi-frame images, and the state estimator adopts multi-state constrained Kalman filter (Multi-State Constraint Kalman Filter, MSCKF) and other filtering methods to simultaneously locate and map construction, so the calculation efficiency is extremely high. The method based on nonlinear optimization is mainly to find common-view feature points from historical multi-frame images and loopback detection ...

Claims

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Application Information

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IPC IPC(8): G01C21/16G01C21/20G01C21/32G06F16/23G06F16/29G06T17/05G06T5/00G06K9/00
CPCG01C21/165G01C21/20G01C21/32G06F16/23G06F16/29G06T17/05G06T5/70
Inventor 高洪臣李骊
Owner BEIJING HUAJIE IMI TECH CO LTD
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