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Looking for a simple, pure inertial motion estimation #334

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pauljurczak opened this issue Sep 17, 2020 · 5 comments · Fixed by #720
Closed

Looking for a simple, pure inertial motion estimation #334

pauljurczak opened this issue Sep 17, 2020 · 5 comments · Fixed by #720

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@pauljurczak
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Is there a way to get a simple, pure inertial motion estimation with RoME.jl o rrelated packages? Ultimate accuracy is not required as I want to use it for motion estimation between camera frames capture events, every 50ms with IMU data rate of 250Hz.

@dehann
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dehann commented Sep 18, 2020

Hi @pauljurczak , yes and no answer -- yes those factors exist but we are not able to share them publicly just yet owing to license restrictions. We are working on getting those available but will still take a bit of time to get that legally sound. Wish we could make them immediately available. In the mean time we are working on integrating ApproxManifoldProducts.jl/IncrementalInference.jl/RoME.jl with Manifolds.jl so that 3D / IMU-derived (non-Gaussian/multimodal) beliefs, and their underlying mechanics, are standardized and performant -- the combination should be pretty good.

xref:

@pauljurczak
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Thank you for responding. In the meantime, do you know another Julia package or C++ library, which does pure inertial motion estimation? Everything I found so far fuses inertial with visual or other sensing modes.

@dehann
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dehann commented Oct 19, 2020

Apologies for the slow reply. Perhaps the fastest thing to do is just make a new factor and embed an ODE solution of the classic inertial navigation solution (akin to preintegrating). This will provide similar or better numerical answers with a little computation slowdown -- it will, however, avoid licensing delays. I will build that for common purpose in the next month or two if I can get to it -- should be pretty straight forward.

@dehann
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dehann commented Nov 9, 2020

Just an update on this, I'm busy adding ODERelative as a new factor that can stand up generic ODE solutions (discrete and consuming sensor data) as a stand-in solution for this and other similar requirements. See JuliaRobotics/IncrementalInference.jl#1020 for ongoing progress. I want to write in a classic INS solution (dynamic bias estimating version) as well, which will be able to solve the problem described in this issue. The native inertial pre-integral (ie more computationally efficient) version will be made public as soon as licensing is sorted out.

@dehann
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dehann commented Nov 14, 2023

see new on-manifold code for factors InertialDynamic and IMUDeltaFactor. These functions work in part either with parametric or nonparametric solving.

This new functionality supercedes previous questions such as:

Note that InertialPose3 may well be used in the future, but currently a new variable RotVelPos is being used as a stand-in solution until all features are consolidated in common.

Next major milestone towards fully consolidated operations will be to complete

@dehann dehann closed this as completed Nov 14, 2023
@dehann dehann modified the milestones: v0.0.x, v0.24.1 Nov 14, 2023
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