7 ms·

Often in textbooks and on here on HN Kalman Filters are praised, but folks from the industry often ridicule Kalman Filters. All People I have interacted with h

Often in textbooks and on here on HN Kalman Filters are praised, but folks from the industry often ridicule Kalman Filters. All People I have interacted with have never used/seen Kalman Filters outside Academica. Do anyone here have industry experience where Kalman Filters is actually used in prod?

aktenlage 3y ago
Yes. Worked in a robotics startup and a tier 1 automotive supplier. In both, variants of the Kalman filter were used for some tasks. They are a simple tool, and simple often works. You just need to know the limitions and know which variant (if any) is best applicable to the problem at hand.
- UncleOxidant 3y ago
  I recently saw "experience with Kalman filters" listed in a job ad from a Robotics company.
- kwant_kiddo 3y ago
  edit: Extensively!! In control theory it seems :) It is just that I keep seeing KF be mentioned on Twitter and blogs etc. for using it in finance.
- AlotOfReading 3y ago
  Done plenty of automotive/robotics by this point and yep. A KF is usually my first (and often only) step between straight up not filtering and finding a controls expert to analyze the system properly. It's cheap, easy, and works well enough that I don't have to think too hard about it.
ms512 3y ago
I used them extensively when I worked on Radar contact tracking. They are an effective tool when used with a good understanding of the limitations.
Randor 3y ago
>> Do anyone here have industry experience where Kalman Filters is actually used in prod? Yes, ship/vessel navigation software heavily use Kalman Filters. Especially on the inputs received from the various position reference sensors.
jgable 3y ago
I built a variant to very successfully estimate state of charge for a large battery pack in a production hybrid-electric vehicle. Often some tweaks from the standard formula are necessary to account for real-world non-linearities, and some creative design work is required to define states in such a way that the Gaussian noise assumption can hold well enough.
NwtnsMthd 3y ago
We develop navigation instrumentation for directional drilling (oil/gas, geothermal, etc.). In these applications you have to estimate the path of the drilling string based on directional measurements and the length of drill pipe you've put into the ground. To take good measurements you have to stop so that rotation and vibration don't corrupt your measurement. We use a type of Kalman Filter to estimate direction and instantaneous dynamics of the drill string, this way the drilling operation no longer needs to stop to get a directional measurement.
onceiwasthere 3y ago
I think this is really wild and interesting. In my experience, they (more like specializations of the Kalman filter) are used almost universally in radar tracking. I'm curious where outside of academia you see ridicule for Kalman Filters?
fest 3y ago
They are widely used in narrow circles :) Two of (arguably the best) open source RC aircraft flight controllers (ArduPilot and PX4) are using extended Kalman filters in their state estimators (essentially sensor fusion that provides attitude/position estimate): https://github.com/ArduPilot/ardupilot/tree/master/libraries/AP_NavEKF2 https://github.com/ArduPilot/ardupilot/tree/master/libraries... https://github.com/PX4/PX4-Autopilot/blob/main/src/modules/ekf2/EKF2.cpp https://github.com/PX4/PX4-Autopilot/blob/main/src/modules/e... I'm not that familiar with cleanflight/betaflight/inav scene to know what the FPV racer flight controllers use.
dabluecaboose 3y ago
Astrodynamics and satellite navigation use kalman filters extensively for orbit determination
visviva 3y ago
In what industry are Kalman filters ridiculed?
- kwant_kiddo 3y ago
  at least in HFT as I am aware, however I see that KF actually IS extensively used elsewhere.
  - comfysocks 3y ago
    KF has been standard stuff in aerospace guidance navigation and control for quite some time. Stock markets are probably too nonlinear to use linear control theory on.
auxym 3y ago
KFs, and more generally state observer systems, are widely used in the field of control systems. I know someone with a PhD in control systems, works for an eVTOL startup, and their title is something like "estimation expert" or "estimation specialist". That is, 100% of their job is designing relatively complex KF-like algorithms that are used to estimate the aircraft state (position, pose, velocity, wind conditions, etc) in real time based on a bunch of sensors.
wenc 3y ago
> folks from the industry often ridicule Kalman Filters. [citation needed] Siemens (SIMATIC PCS 7) https://support.industry.siemens.com/cs/document/109748837/simatic-pcs-7-kalman-configurator-v9-0?dti=0&lc=en-WW https://support.industry.siemens.com/cs/document/109748837/s... Bosch Sensor Fusion https://www.bosch-sensortec.com/products/smart-sensors/bha260ab/ https://www.bosch-sensortec.com/products/smart-sensors/bha26... Kalman filters are not state-of-the-art, but they are fairly simple to implement and are still used.
TickleSteve 3y ago
GPS chipsets use Kalman Filters, its standard practice. I think you have an incorrect perception here.
nh2 3y ago
I am still confused by this too: Lots of typical "industry applications" given for Kalman Filters involve moving objects, like air planes, rockets, and so on. But all these objects generally rotate in some way, rotation is non-linear, and Kalman Filters cannot deal well with nonlinearities. Thus Kalman Filters struggle with rotation, and I haven't really found any good resources that handle this. Do all these applications just skip over the fact that real-world objects can have a rotation/spin, or do they all use more sophisticated filters as suggested in e.g. [1]? [1] https://math.stackexchange.com/questions/2621677/extended-kalman-filter-equation-for-orientation-quaternion https://math.stackexchange.com/questions/2621677/extended-ka...
- oasisaimlessly 3y ago
  The "Integrating Generic Sensor Fusion Algorithms with Sound State Representations through Encapsulation of Manifolds" paper linked from your [1] is indeed the current state of the art. It shows how to use the EKF or UKF for rotation. The naive Kalman filter is only suited for linear problems; extended and unscented Kalman filters (EKF/UKF) are necessary for anything non-linear (including rotation). In any case, they build on the basic KF, so you have to understand that first.
  - nh2 3y ago
    That paper [1] is from 2010. What did "industry" use before that for pysically moving objects? If this is the current state of the art, are there generally-available/open-source libraries existing that implement this and practitioners use for this? The only one I could find is https://github.com/kartikmohta/manifold_cdkf https://github.com/kartikmohta/manifold_cdkf, which currently has 8 Github stars. I also found an approach mentioned in [2] that is to just treat a single rotation angle as linear, and then wrap it around at 180 degrees in between state updates with additional conditional logic. Is this what people did in practice before? I cannot find substantial info on this. How did people use KF on physical objects before 2010? [2]: https://old.reddit.com/r/ControlTheory/comments/d2yrjq/kalman_filter_with_yaw_measurements/ https://old.reddit.com/r/ControlTheory/comments/d2yrjq/kalma...
ColinWright 3y ago
Yes. I was director of Research and Innovation in a company that produces equipment for people to do VTS and VTMIS, which is the maritime equivalent of Air Traffic Control. We track targets (mostly ships, mostly maritime, but not always) and we use Kalman Filters (and variants) extensively. https://en.wikipedia.org/wiki/Kalman_filter#Nonlinear_filters https://en.wikipedia.org/wiki/Kalman_filter#Nonlinear_filter... Contrary to your experience, there was a time when we were ridiculed for not using Kalman Filters, but in the limited niche we inhabited then, our internally developed algorithms out-performed Kalman. But mostly, these days, yes, we use Kalman Filters of various types.
- Randor 3y ago
  >> our internally developed algorithms out-performed Kalman Could you tell me more about this? What other algorithms are used for position tracking and motion estimation. I have seen various ML models... RNN/DNN used. I'm guessing with VTMIS you are doing time-series predictions?
  - ColinWright 3y ago
    Regrets, but no. Developed internally and commercial secrets. 8-(
antegamisou 3y ago
Apple uses EKF (Extended Kalman Filters) for the iPhone's GNSS system: https://www.patentlyapple.com/2020/11/apple-reveals-adding-the-kalman-filter-to-advance-maps-accuracy-for-idevices-especially-moving-vehicles-with-carplay.html https://www.patentlyapple.com/2020/11/apple-reveals-adding-t... I'm 100% sure there's some form of EKF on some loop on AirTags too.
cma 3y ago
Positional tracking on most VR headsets has the fast, low latency updates from the drifty IMU and slower ground truth updates from vision fused together with a Kalman filter. Consumer drones, military drones, and weapons guidance systems use it extensively too.

aktenlage 3y ago

Yes. Worked in a robotics startup and a tier 1 automotive supplier. In both, variants of the Kalman filter were used for some tasks. They are a simple tool, and simple often works. You just need to know the limitions and know which variant (if any) is best applicable to the problem at hand.

UncleOxidant 3y ago
I recently saw "experience with Kalman filters" listed in a job ad from a Robotics company.
kwant_kiddo 3y ago
edit: Extensively!! In control theory it seems :) It is just that I keep seeing KF be mentioned on Twitter and blogs etc. for using it in finance.
AlotOfReading 3y ago
Done plenty of automotive/robotics by this point and yep. A KF is usually my first (and often only) step between straight up not filtering and finding a controls expert to analyze the system properly. It's cheap, easy, and works well enough that I don't have to think too hard about it.

ms512 3y ago

I used them extensively when I worked on Radar contact tracking. They are an effective tool when used with a good understanding of the limitations.

Randor 3y ago

>> Do anyone here have industry experience where Kalman Filters is actually used in prod? Yes, ship/vessel navigation software heavily use Kalman Filters. Especially on the inputs received from the various position reference sensors.

jgable 3y ago

I built a variant to very successfully estimate state of charge for a large battery pack in a production hybrid-electric vehicle. Often some tweaks from the standard formula are necessary to account for real-world non-linearities, and some creative design work is required to define states in such a way that the Gaussian noise assumption can hold well enough.

NwtnsMthd 3y ago

We develop navigation instrumentation for directional drilling (oil/gas, geothermal, etc.). In these applications you have to estimate the path of the drilling string based on directional measurements and the length of drill pipe you've put into the ground. To take good measurements you have to stop so that rotation and vibration don't corrupt your measurement. We use a type of Kalman Filter to estimate direction and instantaneous dynamics of the drill string, this way the drilling operation no longer needs to stop to get a directional measurement.

onceiwasthere 3y ago

I think this is really wild and interesting. In my experience, they (more like specializations of the Kalman filter) are used almost universally in radar tracking. I'm curious where outside of academia you see ridicule for Kalman Filters?

fest 3y ago

They are widely used in narrow circles :) Two of (arguably the best) open source RC aircraft flight controllers (ArduPilot and PX4) are using extended Kalman filters in their state estimators (essentially sensor fusion that provides attitude/position estimate): https://github.com/ArduPilot/ardupilot/tree/master/libraries/AP_NavEKF2 https://github.com/ArduPilot/ardupilot/tree/master/libraries... https://github.com/PX4/PX4-Autopilot/blob/main/src/modules/ekf2/EKF2.cpp https://github.com/PX4/PX4-Autopilot/blob/main/src/modules/e... I'm not that familiar with cleanflight/betaflight/inav scene to know what the FPV racer flight controllers use.

dabluecaboose 3y ago

Astrodynamics and satellite navigation use kalman filters extensively for orbit determination

visviva 3y ago

In what industry are Kalman filters ridiculed?

kwant_kiddo 3y ago
at least in HFT as I am aware, however I see that KF actually IS extensively used elsewhere.
- comfysocks 3y ago
  KF has been standard stuff in aerospace guidance navigation and control for quite some time. Stock markets are probably too nonlinear to use linear control theory on.

auxym 3y ago

KFs, and more generally state observer systems, are widely used in the field of control systems. I know someone with a PhD in control systems, works for an eVTOL startup, and their title is something like "estimation expert" or "estimation specialist". That is, 100% of their job is designing relatively complex KF-like algorithms that are used to estimate the aircraft state (position, pose, velocity, wind conditions, etc) in real time based on a bunch of sensors.

wenc 3y ago

> folks from the industry often ridicule Kalman Filters. [citation needed] Siemens (SIMATIC PCS 7) https://support.industry.siemens.com/cs/document/109748837/simatic-pcs-7-kalman-configurator-v9-0?dti=0&lc=en-WW https://support.industry.siemens.com/cs/document/109748837/s... Bosch Sensor Fusion https://www.bosch-sensortec.com/products/smart-sensors/bha260ab/ https://www.bosch-sensortec.com/products/smart-sensors/bha26... Kalman filters are not state-of-the-art, but they are fairly simple to implement and are still used.

TickleSteve 3y ago

GPS chipsets use Kalman Filters, its standard practice. I think you have an incorrect perception here.

nh2 3y ago

I am still confused by this too: Lots of typical "industry applications" given for Kalman Filters involve moving objects, like air planes, rockets, and so on. But all these objects generally rotate in some way, rotation is non-linear, and Kalman Filters cannot deal well with nonlinearities. Thus Kalman Filters struggle with rotation, and I haven't really found any good resources that handle this. Do all these applications just skip over the fact that real-world objects can have a rotation/spin, or do they all use more sophisticated filters as suggested in e.g. [1]? [1] https://math.stackexchange.com/questions/2621677/extended-kalman-filter-equation-for-orientation-quaternion https://math.stackexchange.com/questions/2621677/extended-ka...

oasisaimlessly 3y ago
The "Integrating Generic Sensor Fusion Algorithms with Sound State Representations through Encapsulation of Manifolds" paper linked from your [1] is indeed the current state of the art. It shows how to use the EKF or UKF for rotation. The naive Kalman filter is only suited for linear problems; extended and unscented Kalman filters (EKF/UKF) are necessary for anything non-linear (including rotation). In any case, they build on the basic KF, so you have to understand that first.
- nh2 3y ago
  That paper [1] is from 2010. What did "industry" use before that for pysically moving objects? If this is the current state of the art, are there generally-available/open-source libraries existing that implement this and practitioners use for this? The only one I could find is https://github.com/kartikmohta/manifold_cdkf https://github.com/kartikmohta/manifold_cdkf, which currently has 8 Github stars. I also found an approach mentioned in [2] that is to just treat a single rotation angle as linear, and then wrap it around at 180 degrees in between state updates with additional conditional logic. Is this what people did in practice before? I cannot find substantial info on this. How did people use KF on physical objects before 2010? [2]: https://old.reddit.com/r/ControlTheory/comments/d2yrjq/kalman_filter_with_yaw_measurements/ https://old.reddit.com/r/ControlTheory/comments/d2yrjq/kalma...

ColinWright 3y ago

Yes. I was director of Research and Innovation in a company that produces equipment for people to do VTS and VTMIS, which is the maritime equivalent of Air Traffic Control. We track targets (mostly ships, mostly maritime, but not always) and we use Kalman Filters (and variants) extensively. https://en.wikipedia.org/wiki/Kalman_filter#Nonlinear_filters https://en.wikipedia.org/wiki/Kalman_filter#Nonlinear_filter... Contrary to your experience, there was a time when we were ridiculed for not using Kalman Filters, but in the limited niche we inhabited then, our internally developed algorithms out-performed Kalman. But mostly, these days, yes, we use Kalman Filters of various types.

Randor 3y ago
>> our internally developed algorithms out-performed Kalman Could you tell me more about this? What other algorithms are used for position tracking and motion estimation. I have seen various ML models... RNN/DNN used. I'm guessing with VTMIS you are doing time-series predictions?
- ColinWright 3y ago
  Regrets, but no. Developed internally and commercial secrets. 8-(

antegamisou 3y ago

Apple uses EKF (Extended Kalman Filters) for the iPhone's GNSS system: https://www.patentlyapple.com/2020/11/apple-reveals-adding-the-kalman-filter-to-advance-maps-accuracy-for-idevices-especially-moving-vehicles-with-carplay.html https://www.patentlyapple.com/2020/11/apple-reveals-adding-t... I'm 100% sure there's some form of EKF on some loop on AirTags too.

cma 3y ago

Positional tracking on most VR headsets has the fast, low latency updates from the drifty IMU and slower ground truth updates from vision fused together with a Kalman filter. Consumer drones, military drones, and weapons guidance systems use it extensively too.