I can’t overemphasize the rewards of starting a running club. About a year ago, I started one nearly by accident— a routine of solo running morphed into a weekly social event. Every Saturday or Sunday five or six of us gather in the mid morning, run five to ten miles, and then have brunch together afterwards. The way I see it, this is a quadruple refill for the soul; a combination of four things that have immense positive impact on your mood:

You’re getting exercise

You’re being social

You’re outside getting sunshine and nature

You’re accomplishing something

The delicious food (and, frequently, drinks) at the end of it don’t hurt either.

With that plug out of the way, I offer below a catalog of twelve routes we’ve found over the last year. Continue reading →

Some kid is pitching his revolutionary startup idea to entrepreneur Elrich Bachman:

Kid: Here it is: Bit… soup. It’s like alphabet soup, BUT… it’s ones and zeros instead of letters. Bachman: {silence} Kid: ‘Cause it’s binary? You know, binary’s just ones and zeroes. Bachman: Yeah, I know what binary is. Jesus Christ, I memorized the hexadecimal times tables when I was fourteen writing machine code. Okay? Ask me what nine times F is. It’s fleventy-five. I don’t need you to tell me what binary is.

We infer that “fleventy-five” is a hexadecimal number, commonly used in coding; presumably it’s 0xF5 (which is not 0x9 times 0xF, as it happens). But instead of saying “eff-five” for the byte 0xF5, Bachman has come up with some kind of novel system for the English-ification of hex digits.

He’s on to something. We have ordinary English words for decimal numbers, with names based on the digits and their place-value. “Seventy” is the word for two-digit chunks starting with the digit seven, for example. It might appear in the number “seventy-three”, or “five hundred seventy-one thousand”; both numbers with a 7 digit in an appropriate place. “Fleventy”, then, would be the number for two-digit chunks starting with F.

Hex only adds more kinds of digits (the symbols A through F). Could we follow Bachman’s lead and add more number-names for the extra digit symbols, and pronounce hex just like a decimal number? Could we have a system that attains the unwieldiness and syllable count of spoken English numbers, with all the respectable seriousness of saying the word “fleventy”?

I’m glad you asked. This has never been done before^{(1)}probably, but fear not; here are the official new number-words for hexadecimal. You may start using them immediately:

Hex Place value

Word

0xA0

“Atta”

0xB0

“Bibbity”

0xC0

“City”

0xD0

“Dickety”

0xE0

“Ebbity”

0xF0

“Fleventy”

I think it would help to solidify this with some examples:

But really, we must go further. What about numbers larger than a byte? We have the words “hundred” and “thousand” for decimal place values higher than ten, so why not something for hex place values higher than 0x10? Say, for multiples of 0x100?

Naturally, we could make yet larger numbers by devising some names for larger place values, and combine them with intermediate values, in the same way that we compose decimal numbers like “thirty thousand” or “six hundred fifty one million”. As in English, place value names could be dropped if you’re feeling brief. We’ll also need hex-digit words for the “teens”.

Try it

I’ll leave you to explore the new naming system with this toy:

How we’ve conversed about hex without a system like this is beyond me. You’re welcome.

This was last week’s project: Building a Kalman filter-based IMU.

IMUs (inertial measurement units) are clever little devices which try to estimate an object’s absolute orientation (and sometimes its position) by examining the forces on the object.

Hobby drone and computer input IMUs generally look at acceleration data (which informs where “down” is), compass data (which points toward north in 3D space), and rate gyro data (which tells the axis and speed of spin). “Down” and “north” in combination can give a pretty accurate constraint on orientation, but unfortunately if there are any lateral forces (wind; turning), they will get mixed in with “down” and distort the estimate. Kalman filters use matrix math to make good use of the gyro data to correct for this. However, a constantly-accelerating drone could still be fooled about where down is.

I’ve tried here to find out whether we can try to model the drone’s translation and take this into account when estimating the orientation. It turns out that even relatively poor and infrequent data about velocity can constrain acceleration— and thus “down”— quite well. The difference in the quality of the estimate is plainly visible.

This is all done by mathematically simulating a 3D moving object using ordinary dynamics and battering it with Gaussian random forces, and then predicting what data a noisy sensor might return. A predictor algorithm using a Kalman filter (which has no knowledge about the original state) attempts to recover the true state to the best of its ability. The truth is rendered white here, and the estimate in red.

At the end you can see the same algorithm running on actual sensors. The real thing doesn’t use GPS yet, but the prediction is still pretty decent! (There is not that much sustained acceleration to throw it off in this video).

I’ve done some other cool things with the code which perhaps I’ll write up in the future: Among them are a process noise model based on Gaussian random walks, and a nice extension of it to quaternions (which has dramatic impact on the quality of the estimate!) I also make use of automatic differentiation, which makes a linearized extended Kalman filter (EKF) particularly easy and robust to implement.