Rudolf Kálmán Has Died
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Rudolf Kálmán Has Died
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Re: Rudolf Kálmán Has Died
#2Kalman filters are really neat. I wrote one when learning C a while ago and it is just cool what some matrix math can do with practical data. https://github.com/lacker/ikalman
Although I guess I should have been calling it a "Kálmán filter" this whole time.
Re: Rudolf Kálmán Has Died
#3Kalman filters are really neat. I wrote one when learning C a while ago and it is just cool what some matrix math can do with practical data. https://github.com/lacker/ikalman Although I guess I should have been calling it a "Kálmán filter" this whole time.
Interesting. I don't see generic Kalman filter implementations too often. Thanks for sharing.
I've always found that determining where to put outputs from disparate sensors as opposed to just filtering a single observation like the GPS output in your example is challenging. Have you tried extending this to include input from other sensors (e.g. accelerometer, gyroscope, magnetometer, etc.)?
Re: Rudolf Kálmán Has Died
#4Kalman filters are really neat. I wrote one when learning C a while ago and it is just cool what some matrix math can do with practical data. https://github.com/lacker/ikalman Although I guess I should have been calling it a "Kálmán filter" this whole time.
I've been using it lately for my thesis. Good job!
Re: Rudolf Kálmán Has Died
#5I was waiting for this headline. Someone edited his wikipedia article last week, but provided no source and no articles were published yet.
The Kalman filter is a fantastic tool. I use it and the particle filter regularly. Both are ubiquitous in robotics and cyber-physical systems and incredibly powerful tools.
Interestingly, Kalman wasn't able to publish it in a prestigious journal at the time and had to settle for a lesser known one.
EDIT: Forgot to finish my sentence...
Re: Rudolf Kálmán Has Died
#6Just last week I needed to smooth out a display reading on an oven controller. The RTD was being read way too fast so I'd get a lot of flicker between values due to ADC resolution.
In the back of my head I remembered one word: Kalman. This line of code fixed it right up:
static float display_temp = 0;
display_temp += 0.04 * (adc_temp - display_temp);Re: Rudolf Kálmán Has Died
#7Just last week I needed to smooth out a display reading on an oven controller. The RTD was being read way too fast so I'd get a lot of flicker between values due to ADC resolution. In the back of my head I remembered one word: Kalman. This line of code fixed it right up: static float display_temp = 0; display_temp += 0.04 * (adc_temp - display_temp);
Well, I guess, but, I mean, really… that's a first-order low-pass filter.
Re: Rudolf Kálmán Has Died
#8Just last week I needed to smooth out a display reading on an oven controller. The RTD was being read way too fast so I'd get a lot of flicker between values due to ADC resolution. In the back of my head I remembered one word: Kalman. This line of code fixed it right up: static float display_temp = 0; display_temp += 0.04 * (adc_temp - display_temp);
That's not a kalman filter.
Re: Rudolf Kálmán Has Died
#9[deleted]
Re: Rudolf Kálmán Has Died
#10Just last week I needed to smooth out a display reading on an oven controller. The RTD was being read way too fast so I'd get a lot of flicker between values due to ADC resolution. In the back of my head I remembered one word: Kalman. This line of code fixed it right up: static float display_temp = 0; display_temp += 0.04 * (adc_temp - display_temp);
That's just a linear interpolation between two values: take 96% of the current display value plus 4% of the new value from the ADC, which is the same as finding 4% of the way between the two values. It's a simple generalization of the arithmetic mean, which is the special case of 50%.
I'm skeptical that anyone sane would credit this obvious idea should to one particular person, which is why it can't be the Kalman filter.