Git Product home page Git Product logo

ingvio's People

Contributors

changwuliu avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

ingvio's Issues

Clarification on RTK

In the paper, at the end of section V, you make the following statement:

The meter-level difference of the estimated path of GVINS [23] or InGVIO to the RTK ground truth is attributed to the inaccuracy of the atmospherical propagation models of the pseudo range.

If I am not mistaken, GVINS and InGVIO are using only pseudo-range and pseudo-range rate / Doppler shift measurements and no phase-range measurements, which would require ambiguity resolution. Did you exclude phase-range measurements from the RTK ground truth computation? If not, I would expect the meter-level difference because of considering phase-range measurements in RTK and less about the atmospherical modeling. Of course, improving atmospherical modeling will improve the result, but probably not close the gap to RTK in my view.

Clarification on proposition 2

Thanks a lot for providing the code on github and the paper on arxiv. I am studying the paper carefully and got stuck in section B on conditional infinitesimal symmetries of GVIO. If I understand it correctly, proposition 2 addresses the dot product of the pseudo-range rate measurements. It derives the infinitesimal symmetry of the pseudo-range rate measurements. What about the norm of the pseudo-range measurements? Is the infinitesimal symmetry of pseudo-range given by the one of the rate?

About using vins-fusion to test the fw-dataset.

Sorry to disturb you.Have you ever used vins-fusion to test your dataset only in mode stereo+imu or the global-fusion mode. I found that the drift is so big.Maybe my config yaml is not right.Hope that if you have tested before,you can solve my problem.Thanks.

Question about invariant and consistent

Hi, great job and thanks for your open source!

I would like to ask that what is the difference between invariant and consistent in the context of EKF?

Hope to hear from you!

The derivation was based which form of quaternion? JPL or Hamilton

Hello, I wanna know that your derivation of all equations was in form of JPL or Hamilton quaternion. Because you referred to OpenVINS and it is based on JPL quaternion. Was the state transition matrix F also derived in form of JPL? I am looking forward to your reply.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.