Weight-optimized dot-line comprehensive visual inertia odometer method

An odometer and weight technology, applied in the field of computer vision, can solve the problems of solution results and accuracy effects, system failures, algorithm robustness and stability effects, etc.

Active Publication Date: 2020-11-24
BEIHANG UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

However, in the visual part of the inertial visual odometer, due to environmental factors such as poor lighting and environmental texture conditions, the system fails to collect enough feature points, which has a great impact on the robustness and stability of the algorithm. big impact
In addition, the mismatch in feature matching will also have a negative impact on the solution results and accuracy of the system

Method used

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  • Weight-optimized dot-line comprehensive visual inertia odometer method
  • Weight-optimized dot-line comprehensive visual inertia odometer method
  • Weight-optimized dot-line comprehensive visual inertia odometer method

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Embodiment Construction

[0035] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0036] The embodiment of the present invention discloses a weight-optimized point-line comprehensive visual-inertial odometer method, such as figure 1 shown, including the following specific steps:

[0037] S1. Use the camera and IMU mounted on the carrier to collect environmental information and motion information, select key frames, perform sliding window edge processing on the key frames, and realize the extraction and managemen...

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Abstract

The invention discloses a weight-optimized dot-line comprehensive visual inertia odometer method which comprises the following steps: acquiring environmental information and motion information by using a camera and an IMU carried by a carrier, and realizing extraction and management of dot characteristics and linear characteristics and pre-integration of IMU motion information; obtaining an initial pose calculation target function by using the point features, the linear features and the residual error of the IMU; optimizing a target function model formed by each residual error by utilizing thenonlinear weight suppression instability characteristic based on the word frequency; and calculating a carrier position and a motion condition by utilizing the optimized target function. The weight-optimized dot-line comprehensive visual inertia odometer method solves the problem that the number of features in a weak texture scene is small by using a feature straight line, optimizes a feature residual model by using a nonlinear weight, and realizes stable and effective operation of a visual inertia odometer in the weak texture scene.

Description

technical field [0001] The invention relates to the technical field of computer vision, and more specifically relates to a weight-optimized point-line comprehensive visual-inertial odometer method. Background technique [0002] Visual-inertial odometry is one of the common integrated navigation methods, which has the characteristics of low cost, small size and convenience. In recent years, with the development of small platforms, visual inertial odometry has been widely used, and the requirements for algorithm accuracy, applicable environment and stability are also increasing. However, in the visual part of the inertial visual odometer, due to environmental factors such as poor lighting and environmental texture conditions, the system fails to collect enough feature points, which has a great impact on the robustness and stability of the algorithm. big impact. In addition, the mismatching that occurs during feature matching will also have a negative impact on the solution r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/16G01C3/00G01C22/00
CPCG01C3/00G01C21/16G01C22/00
Inventor 赵龙赵毅琳
Owner BEIHANG UNIV
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