Manifold pre-integration-based visual inertial milemeter posture estimation method and device

A pose estimation and pre-integration technology, applied in measurement devices, navigation calculation tools, instruments, etc., can solve problems such as cumulative drift of inertial sensors, and achieve the effects of reducing time drift, suppressing error propagation, and high positioning accuracy

Active Publication Date: 2018-11-16
SOUTH CHINA UNIV OF TECH
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But the inertial sensor will have the problem

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  • Manifold pre-integration-based visual inertial milemeter posture estimation method and device
  • Manifold pre-integration-based visual inertial milemeter posture estimation method and device
  • Manifold pre-integration-based visual inertial milemeter posture estimation method and device

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Embodiment 1

[0107] The visual-inertial odometer system structure of the present embodiment is as follows figure 1 As shown, in the visual-inertial odometry system, the key steps are to design the processing method of the inertial information and the joint optimizer that combines the visual and inertial information. The main role of the joint optimizer is to serve as the interface of the two positioning subsystems to realize the system combination, and to perform data fusion on the positioning information received by the system. In the research process of the inertial subsystem, the pre-integration method on the manifold plays an important role. After the inertial information is obtained, the inertial measurement value is pre-integrated on the Riemannian manifold to form a constraint between two frames of visual measurement information. The joint optimizer is used to jointly optimize the visual information and inertial information, thereby improving the positioning accuracy of the visual-...

Embodiment 2

[0194] Such as Figure 6 As shown, this embodiment provides a visual-inertial odometer pose estimation device based on manifold pre-integration, the device includes an initialization module, an inertial data alignment module, a visual optical flow pose estimation module, an inertial pre-integration module, the first One optimization module and the second optimization module, the functions of each module are as follows:

[0195] The initialization module is used to complete the initialization of the visual-inertial odometry system;

[0196] The inertial data alignment module is used to obtain all inertial data between two frames of visual images by marking time stamps on visual data and inertial data;

[0197] The visual optical flow pose estimation module is used to perform LK optical flow method matching on the visual image obtained in each frame with the last frame of visual image stored in the system, to obtain tracking point information between two frames of visual images...

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Abstract

The invention discloses a manifold pre-integration-based visual inertial milemeter posture estimation method and device. After finishing the initialization of the visual inertial milemeter system, themethod comprises: visual inertial data alignment, visual optical flow position posture calculation, inertial pre-integration, visual and inertial joint optimization, window marginalization and aboveprocess repetition so that continuous estimation of camera postures is realized. Compared with the single visual milemeter system, the manifold pre-integration-based visual inertial milemeter system has a higher positioning precision, effectively utilizes inertial information in the milemeter system based on the manifold pre-integration algorithm, inhibits noise propagation of the system and reduces the influence of the inertial zero drift on the positioning accuracy of the milemeter.

Description

technical field [0001] The invention relates to a method for estimating a pose of a visual-inertial odometer, in particular to a method and a device for estimating a pose of a visual-inertial odometer based on manifold pre-integration, belonging to the field of autonomous navigation. Background technique [0002] Visual metrology (VO) and simultaneous localization and mapping (SLAM) have become important components of autonomous navigation research, as they provide convenient and reliable alternatives to classic robot / vehicle localization solutions. Compared to environment-aware sensors such as laser scanners, cameras have the advantage of being lightweight, detecting most solid materials, and taking readings at a fairly high frequency. Therefore, they are crucial in navigation, motion planning and obstacle avoidance. However, in typical applications, the camera's field of view is limited. Close obstacles obscure most of the scene, unstructured surfaces often lack visual c...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01C21/16
CPCG01C21/165G01C21/20
Inventor 刘富春苏泫
Owner SOUTH CHINA UNIV OF TECH
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