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SLAM (Simultaneous Localization and Mapping)-based positioning method and system

A positioning method and repositioning technology, applied in image data processing, instruments, navigation computing tools, etc., can solve the problems of limited application range of binocular positioning, high signal requirements, difficulty in improving positioning efficiency and accuracy, etc.

Active Publication Date: 2018-05-04
UISEE TECH BEIJING LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In smart home or smart wearable scenarios, positioning is widely used. However, GPS positioning, AGPS positioning base, station positioning and WiFi positioning are usually used for positioning, which requires high signal and is easy to be interfered. Positioning accuracy is low and error is large
[0005] In the prior art, binocular SLAM positioning has high requirements on the quality of positioning data, and low-quality positioning data cannot be processed. Instead, only repeated binocular positioning and filtering of low-quality positioning data are used to solve the problem of positioning accuracy.
In this way, the application range of binocular positioning is limited, and it is difficult to improve positioning efficiency and accuracy

Method used

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  • SLAM (Simultaneous Localization and Mapping)-based positioning method and system

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Embodiment Construction

[0049] Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described here.

[0050] exemplary method

[0051] The positioning method based on SLAM of the present invention comprises following basic steps:

[0052] Calculate the initial position of the camera in the global map, wherein the global map refers to the binocular SLAM global map;

[0053] Extract a local map from the global map based on the initial position of the camera;

[0054] match the current frame with a local map point; and

[0055] Monocular SLAM positioning is triggered based on the matching result of the current frame and local map points, wherein the monocular...

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Abstract

The invention discloses an SLAM (Simultaneous Localization and Mapping)-based positioning method and system. The method disclosed by the invention comprises the following steps: calculating an initialposition of a camera in a global map, wherein the global map refers to a binocular SLAM global map; extracting a local map from the global map according to the initial position of the camera; matching a current frame and a local map point; based on a matching result of the current frame and the local map point, triggering monocular SLAM positioning, wherein the monocular SLAM positioning is usedfor generating a new map point through a monocular camera and positioning. The SLAM-based positioning method and system can be used for triggering the monocular SLAM positioning to supplement the mappoint when the positioning quality is poor, the positioning accuracy is increased and the positioning efficiency is improved; under the condition that the positioning quality is good and positioning is lost, basic map positioning is carried out.

Description

technical field [0001] The present application relates to the field of artificial intelligence, in particular to a positioning method and device for unmanned driving. Background technique [0002] Visual SLAM is one of the hotspots of SLAM research in the 21st century. On the one hand, it is because the vision is very intuitive. On the other hand, due to the increase in the processing speed of CPU and GPU, many visual algorithms that were previously considered impossible to real-time can be implemented at speeds above 10Hz. run. The improvement of hardware has also promoted the development of visual SLAM. [0003] In terms of sensors, visual SLAM research is mainly divided into three categories: monocular, binocular (or multi-purpose), and RGBD. There are other special cameras such as fisheye and panorama, but they belong to the minority in research and products. In addition, visual SLAM combined with an inertial measurement unit (Inertial Measurement Unit, IMU) is also o...

Claims

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Application Information

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IPC IPC(8): G01C21/20G06T7/70
CPCG01C21/20G06T7/70G06T2207/10016
Inventor 蔡少骏孟超
Owner UISEE TECH BEIJING LTD
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