Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Pose estimation method for a visual inertial navigation odometer based on a sparse feature method

A sparse feature and pose estimation technology, which is applied in the field of pose estimation of visual inertial navigation odometry, and can solve the problems of increasing the smoothness of the estimated trajectory and the inability of quadrotors to carry large computing equipment.

Inactive Publication Date: 2019-08-23
ZHEJIANG UNIV
View PDF7 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the four-rotor aircraft cannot be equipped with large-scale computing equipment, and proposes a method for estimating the pose of a visual-inertial navigation odometer based on the sparse feature method. The latitude matrix inversion step is replaced by the QR decomposition method with faster calculation speed, and the line feature is introduced to increase the smoothness of the estimated trajectory to build a new visual inertial odometry framework

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pose estimation method for a visual inertial navigation odometer based on a sparse feature method
  • Pose estimation method for a visual inertial navigation odometer based on a sparse feature method
  • Pose estimation method for a visual inertial navigation odometer based on a sparse feature method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0064] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of arrangements consistent with aspects of the invention as recited in the appended claims. Each embodiment in this specification is described in a progressive manner.

[0065] Such as figure 1 As shown, the present invention provides a method for estimating the pose of a visual-inertial navigation odometer based on the sparse feature method, comprising the following steps:

[0066] (1) When the second frame image arrives, integrate the acceleration and angular velocity output by all inertial sensing units between the second frame image and the first frame image to obtain the initial value of the system state, and use the direction of gravity to define the initial coo...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a pose estimation method for a visual inertial navigation odometer based on a sparse feature method. The method mainly comprises system initialization, inertial sensing unit state transfer, image feature point tracking, inertial sensing unit error item construction, system state quantity marginalization, visual measurement model error item construction and observability matrix constraints. the square root information filtering method is used to replace a high-latitude matrix inversion step of the traditional filtering method with a QR decomposition method with a fastercalculation speed, and line features are introduced at the same time to increase the smoothness of the estimated trajectory so as to construct a brand new visual inertial navigation odometer framework.

Description

technical field [0001] The invention relates to the field of state estimation of a quadrotor aircraft, in particular to a method for estimating a pose of a visual inertial navigation odometer based on a sparse feature method. Background technique [0002] The quadrotor aircraft has the advantages of small size, good maneuverability, and vertical take-off and landing. It can easily take off and perform tasks vertically in complex terrain such as mountains, and its high maneuverability enables it to quickly plan complex trajectories to avoid dense traffic. Obstacle avoidance can complete actions that fixed-wing aircraft cannot complete, so it has a wide range of applications in fields such as aerial photography, surveying and mapping, logistics, security, and agriculture. Generally speaking, the algorithm modules of quadrotor aircraft mainly include control, planning, pose estimation and decision-making, etc., among which accurate pose information is the basis of all algorithm...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/16G01C22/00
CPCG01C21/165G01C22/00
Inventor 许超万旭东
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com