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Positioning method based on monocular vision odometer and IMU fusion

A monocular vision and positioning method technology, applied in the field of mobile robots, can solve the problems of affecting positioning effect, IMU cumulative error data fusion, poor robustness, etc.

Active Publication Date: 2021-05-04
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of poor positioning effect and robustness of monocular vision under the influence of dynamic objects in the positioning process, and at the same time solve the problem of IMU cumulative error and reduce the error of data fusion caused by noise outliers in complex noise environments problem, a positioning method based on the fusion of monocular visual odometer and IMU is proposed

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  • Positioning method based on monocular vision odometer and IMU fusion
  • Positioning method based on monocular vision odometer and IMU fusion
  • Positioning method based on monocular vision odometer and IMU fusion

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Embodiment Construction

[0083] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0084] Before describing the specific embodiments of the present invention, in order to make the scheme of the present invention more clear and complete, at first the abbreviations and key term definitions that appear in the present invention are explained:

[0085] IMU: Inertial measurement unit (English: Inertial measurement unit, IMU for short) is a device that measures the three-axis attitude angle (or angular rate) and acceleration of an object.

[0086] 2D-2D algorithm: epipolar constraint algorithm.

[0087] 3D-3D algorithm: English: Iterative Closest Point, referred to as ICP, refers to the iterative closest point algorithm.

[0088] Such as figure 1 As shown, the present invention provides a positioning method based on monocular visual odometer and IMU fusion, comprising the following steps:

[0089] S1: Use the monocular camera to collect im...

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Abstract

The invention discloses a positioning method based on monocular vision odometer and IMU fusion. The method comprises the following steps of S1, acquiring image information and transmitting the image information to a robot main control system, and performing feature point processing on an image; S2, acquiring a three-axis acceleration and a three-axis angular speed of the IMU and processing to obtain IMU data, and transmitting the IMU data to a robot main control system; S3, performing feature point matching by using the robot main control system to obtain visual odometer data; S4, fusing the IMU data and the visual odometer data to obtain a fused robot pose; and S5, repositioning the pose of the robot subjected to loopback. According to the positioning method, multi-sensor data fusion is carried out by using a filtering idea to further optimize positioning information, the IMU and the monocular visual odometer are combined, mutual defects are overcome, respective advantages are reserved, and the visual positioning robustness of the monocular visual odometer in a dynamic environment is improved.

Description

technical field [0001] The invention belongs to the technical field of mobile robots, and in particular relates to a positioning method based on fusion of a monocular vision odometer and an IMU. Background technique [0002] Multi-sensor fusion is one of the future development directions in robot positioning and navigation, and in multi-sensor fusion, the fusion of IMU and visual information is a very important part. Because monocular cameras have the advantages of low cost and small size, they are widely used in robot vision positioning. However, the monocular camera cannot obtain depth information, so it lacks scale information. The pure visual positioning system has poor robustness and low positioning accuracy in a dynamic environment. At the same time, the filtering idea is used to fuse IMU data and monocular visual odometer data. The complex noise environment will produce irresistible interference to the fusion data, so it is urgent to provide a method to solve these p...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01C22/00
CPCG01C21/20G01C22/00
Inventor 于慧君蓝天保彭倍魏敦文周吴
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA