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A method for implementing a mobile-based semantic slam system

A system implementation and mobile terminal technology, applied in image analysis, image enhancement, instruments, 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 expansion capabilities. Inexpensive, good performance results

Active Publication Date: 2020-07-03
XIAMEN UNIV
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  • Abstract
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  • Claims
  • Application Information

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

Method used

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  • A method for implementing a mobile-based semantic slam system
  • A method for implementing a mobile-based semantic slam system
  • A method for implementing a mobile-based semantic slam system

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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

A method based on mobile semantic SLAM system involves the integration of SLAM system construction and point cloud semantic analysis.Including the following steps: 1) Solving the camera posture based on the characteristics of improved FAST and LDB features; 2) the back -end optimization obtains accurate point cloud position and camera posture; 3) return to the ring test; 4) the construction of global point cloud maps for construction; 5) Use the SLAM system to realize the augmented reality system; 6) Use semantic segmentation to achieve 3D point cloud synonyms; 7) Optimization of mobile semantic SLAM system based on the mobile terminal.For environmental cognition and augmented reality in the flexible indoor and outdoor scenarios, especially in the fields of driverless driving and path planning, it obtains low cost and good performance solutions, and has a wide range of application value and expansion capabilities.

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 Patents(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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