Method for realizing semantic SLAM system based on mobile terminal

A system implementation and mobile terminal technology, applied in image data processing, instruments, character and pattern recognition, etc., can solve problems such as relatively demanding hardware computing capabilities, difficulty in handling mobile devices, scale and precision drift, etc., and achieve wide application value and Scalability, low cost, good performance results

Active Publication Date: 2018-06-29
XIAMEN UNIV
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

First of all, traditional SLAM requires a large amount of calculations, which requires more demanding hardware computing power, and mobile devices are difficult to cope with; second, monocular SLAM also has scale and precision drift (Strasdat, Montiel, A.J.Davison, Scale drift-aware large scalemonocular SLAM, RSS 2006), the error is relatively large, especially when modeling large outdoor scenes, it often fails (Quan Meixiang, Park Songhao, Li Guo. Review of Visual SLAM [J]. Journal of Intelligent Systems, 2016, 11( 6):768-776); Finally, there are relatively few studies that can simultaneously perform environment modeling and semantic segmentation

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  • Method for realizing semantic SLAM system based on mobile terminal
  • Method for realizing semantic SLAM system based on mobile terminal
  • Method for realizing semantic SLAM system based on mobile terminal

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Embodiment Construction

[0041] The following embodiments will further illustrate the present invention in conjunction with the accompanying drawings.

[0042] 1. Basic concepts

[0043] (1) Semantic SLAM

[0044] People can intuitively perceive the things displayed on the point cloud map, but for the robot, there is no difference between the three-dimensional points on the map, and the robot cannot recognize what exists in the current map. After semantic segmentation, the robot can distinguish the semantic categories in the point cloud. Therefore, the construction of semantic maps is very important for SLAM.

[0045] The point cloud is constructed by the RGBD camera and the three-dimensional point cloud features are extracted, and input to the pre-stored point cloud database for fast retrieval. If the point cloud is successfully matched with the object in the database, this point cloud is stored in the current map. Andrew uses the idea of ​​two-dimensional image retrieval to retrieve three-dimensio...

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Abstract

The invention provides a method for realizing a semantic SLAM system based on a mobile terminal and relates to fusion of construction of an SLAM system and point cloud semantic analysis. The method comprises the following steps: 1) solving a camera pose based on an improved FAST and LDB characteristic point method; 2) carrying out back-end optimization to obtain an accurate point cloud position and an accurate camera pose; 3) carrying out loopback detection; 4) constructing a global point cloud map; 5) realizing an augmented reality system by utilizing the SLAM system; 6) realizing 3D point cloud semantic segmentation by utilizing semantic segmentation; and 7) optimizing the semantic SLAM system based on the mobile terminal. Aiming at environmental cognition in flexible indoor and outdoorscenes and augmented reality demands, especially in the fields of unmanned driving, path planning and the like, a solution low in cost and good in performance is obtained, and the method has extensiveapplication value and expansion capability.

Description

technical field [0001] The present invention relates to the integration of SLAM system construction and point cloud semantic analysis, in particular to a method for realizing a semantic SLAM system based on a mobile terminal. Background technique [0002] With the continuous development of artificial intelligence and computer vision technology, more and more cutting-edge technologies are applied to real products. Technologies such as robotics, face recognition, intelligent algorithms, and 3D reconstruction have gradually integrated into people's lives. During the two sessions held in March this year, the government even made robotics and artificial intelligence a key development industry in the next few years. [0003] SLAM technology has good application prospects in the fields of robotics, autonomous driving, virtual and augmented reality. Among many computer vision and artificial intelligence technologies, SLAM research continues to be hot. In recent years, more and more...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06T7/73G06T19/00G06K9/62
CPCG06T7/11G06T7/73G06T19/006G06T2207/10028G06F18/23
Inventor 纪荣嵘郭锋张源
Owner XIAMEN UNIV
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