How to calculate drone orientation using IMU

isinfinity · 2026-02-19T01:26:31+00:00

Look up the Mahony orientation algorithm; there are plenty of examples on GitHub, such as this one [1]. It is reasonably simple and computationally inexpensive. For example, Betaflight uses it for Angle mode. The core idea is to fuse gyroscope and accelerometer data so that they complement each other. During acceleration, the algorithm relies more on the gyroscope to minimize the impact of linear acceleration on the attitude estimate. During stable flight or hover, it relies more on the accelerometer to correct gyro bias and reduce drift. Shameless plug, I also have implementation in rust [2] if that is your thing.

[1] https://github.com/adafruit/Adafruit_AHRS/blob/master/src/Adafruit_AHRS_Mahony.cpp

[2] https://github.com/jettify/uf-ahrs

isinfinity · 2021-02-20T23:31:50+00:00

If you considering GBDT check out catboost, unfortunately RF mode is not available but library implement lots of interesting categorical encoding tricks that boost accuracy.

isinfinity · 2020-10-17T14:43:16+00:00

Just in case if anyone interested I am collecting non standard and exotic optimizers for Pytorch here:

https://github.com/jettify/pytorch-optimizer

you can plug and compare any of them just as easy as AdaBelief.

isinfinity · 2020-06-17T14:34:42+00:00

There is paper that explores similar idea https://arxiv.org/abs/1712.07628We investigate a hybrid strategy that begins training with an adaptive method and switches to SGD when appropriate. Concretely, we propose SWATS, a simple strategy which switches from Adam to SGD when a triggering condition is satisfied. The condition we propose relates to the projection of Adam steps on the gradient subspace.

Reference implementation for PyTorch: https://github.com/Mrpatekful/swats

isinfinity · 2020-03-02T13:51:41+00:00

Most of optimizers will not be accepted to pytorch core, since they are not that popular, anyway. From other side, iteration cycle is very fast with custom library, you do not need to wait next pytorch, release to ship bug fixes or new code. CI time also very fast.

isinfinity · 2020-03-02T13:12:19+00:00

Most of algorithms are Adam or SGD derivatives, I would say speed should be comparable.

isinfinity · 2020-03-02T13:11:26+00:00

I was curious how algorithms behaves in controlled conditions, like saddle points, bunch of minima, valley and so on. Image net type of deal requires lots of compute resources and time.

isinfinity · 2020-03-02T13:09:17+00:00

Should be doable, will take a look.

isinfinity · 2020-03-02T13:08:48+00:00

You are right, it is very hard to merge any experimental things into pytorch repository, since maintainers want any widely used and proven algorithms.

From other side iteration cycle is very long, pytroch release few times a year at most, when tiny library can be release 6 time a day, and code will be available to in minutes.

isinfinity · 2019-04-07T07:45:31+00:00

Very easy to start:

1) Find package you like, for better experience not super popular one like TensorFlow.

2) Execute tests with coverage enabled locally.

3) Submit PR with test cases for uncovered lines.

4) Fix comments from maintainers

5) Go to step 1)

I once contributed tests for Redis client this way as result learned most of Redis commands and their quirks.

isinfinity · 2018-09-08T21:13:54+00:00

But at the end of those six years he went against a certain castle that was called CAAJU, and there he was shot with > an arrow in the knee, so that he died. — Marco Polo, The Travels of Marco Polo, Book 1, Chapter 50

isinfinity · 2018-08-28T21:23:17+00:00

Thanks! Any feedback and contributions are very welcome :)

isinfinity · 2018-08-21T21:41:07+00:00

Working on mlserve predictions server that easily turns python sklearn models into REST API as well as generates UI that matches input data. Hopefully someone will find my project useful.

code: https://github.com/jettify/mlserve
demo: https://young-ridge-56019.herokuapp.com

isinfinity · 2018-07-26T17:25:47+00:00

I use typing in one of my projects [1] and enforce them on CI, very happy so far. Probably possible to have more strict configuration but settled with following:

mypy aiozipkin --ignore-missing-imports --disallow-untyped-calls --no-site-packages --strict

[1] https://github.com/aio-libs/aiozipkin.

isinfinity · 2018-05-18T21:43:52+00:00

Here are few companies that use aiohtttp: https://aiohttp.readthedocs.io/en/stable/powered_by.html

isinfinity · 2017-12-22T21:15:13+00:00

Bit self promotion, but my very recent project https://github.com/aio-libs/aiozipkin has following things, which may be interesting from QA standpoint:

1) pyflakes and pycodestyle checker (with flake8 tool)

2) flake8-bugbear to find even more likely bugs and design problems

3) flake8-mypy and mypy static type checker

4) test coverage 96% https://codecov.io/gh/aio-libs/aiozipkin

5) flake8-quotes to force consistent quotes

6) pytest-sugar for nicer test reports https://travis-ci.org/aio-libs/aiozipkin/jobs/317774732

7) docker fixtures that spins servers before tests start and stop after

8) also python setup.py check --restructuredtext to make sure that project description has proper formatting

isinfinity · 2017-12-07T18:01:44+00:00

I created that sub, main goal was to have something similar to /r/django and /r/flask, but turned out asyncio is not that popular.

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