Realizing method and system of vision inertial mileometer

An implementation method and odometer technology, applied in the field of computer vision, which can solve the problems of high power consumption, poor real-time performance, and difficulty in processing power.
CN108489482AActive Publication Date: 2018-09-04SHICHEN INFORMATION TECH SHANGHAI CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHICHEN INFORMATION TECH SHANGHAI CO LTD
Publication Date
2018-09-04

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Abstract

The invention embodiment discloses a realizing method and a system of a vision inertial mileometer. The realizing method comprises following steps: 1, a camera is adopted for real-time acquisition ofimage data, and an IMU is adopted to collect gyroscope and acceleration data; 2, a scene initialization module is adopted to establish an initial space three-dimensional map of a vision inertial mileometer system; 3, a map expansion module is adopted for real-time updating of the initial space three-dimensional map; and 4, an attitude estimation module is used for receiving the position and the attitude of equipment corresponding to each image frame. According to the realizing method, the scene initialization module is adopted to realize system initialization process high in robustness; the attitude estimation module is adopted to realize position and attitude optimization based on vision information and IMU information combined constraints; a repositioning module is adopted for failure treatment and repositioning algorithm, and equipment real-time position and attitude information are obtained. The invention embodiment also discloses a vision inertial mileometer system.
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Description

technical field

[0001] The embodiment of the present invention relates to a computer vision technology, in particular to a method for realizing a visual inertial odometer. The embodiment of the present invention also relates to a visual-inertial odometer system. Background technique

[0002] Real-time tracking of the position and attitude of devices in an unknown environment is one of the core issues in the fields of augmented reality, virtual reality, navigation and control, mobile robots, unmanned driving, and drones. As the most common method to solve such problems, Simultaneous Localization and Mapping (SLAM) has also been widely studied in related fields such as robotics and computer vision. Recently, localization algorithms based on the fusion of computer vision and inertial measurement units have received increasing attention due to their low cost, high accuracy, and strong complementarity. This method of using the device's own camera and IMU (inertial measurement u...

Claims

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